Section 7 OF THE GOLDEN SAYINGS OF EPICTITUS, BY EPICTITUS 141. Ponder on this, on these convictions, on these words. Fix thine eyes on these examples, if thou wouldst be free, if thou hast thine heart set upon the matter according to its worth, and what marvel if thou purchase so great a thing at so great and high a price. For the sake of this that men deem liberty, some hang themselves, others cast themselves down from the rock. I, time has been when whole cities came utterly to an end, while for the sake of freedom that is true and sure and unassailable, dost thou grudge to God what he gave when he claims it? Will thou not study, as Plato saith, to endure, not death alone, but torture, exile, stripes, in a word, to render up all that is not thine own? Else thou wilt be a slave amid slates, worth thou ten thousand times a consul? I, not a wit the less, though thou climb the palace steps, and thou shalt know how true the saying of Cleanthus, that though the words of philosophers may run counter to the opinions of the world yet have they reason on their side. 142. Ask how a man should best grieve his enemy, Epictetus replied, by setting himself to live the noblest life himself. 143. I am free. I am a friend of God ready to render him willing obedience. Of all else I may sit store by nothing, neither by my known body, nor possessions, nor office, nor good report, nor, in a word, ought else beside, for it is not his will that I should so set store by these things. Had it been his pleasure he would have placed my good therein, but now he hath not done so, therefore I cannot transgress one jot of his commands. In everything hold fast to that which is thy good, but to all else, as far as is given thee, within the measure of reason only, contented with this alone. Else thou wilt meet with failure, ill success, let, and hindrance. These are the laws ordained of God, these are his edicts, these a man should expound and interpret, to these submit himself, not to the laws of misurias and caches. 144. Remember that not the love of power and wealth sets us under the heel of others, but even the love of tranquility, of leisure, of change of scene, of learning in general, it matters not what the outward thing may be. To set store by it is to place thyself in subjection to another. Where is the difference, then, between desiring to be a senator and desiring not to be one, between thirsting for office and thirsting to be quit of it? Where is the difference between crying, woe is me, I know not what to do, bound hand and foot as I am to my books, so that I cannot stir, and crying, woe is me, I have not time to read, as though a book were not as much an outward thing and independent of the will as office and power and the receptions of the great? Or what reason hast thou, tell me, for desiring to read, for if thou name at nothing beyond the mere delight of it, or gaining some scrap of knowledge, thou art but a poor, spiritless knave, but if thou desirest to study to its proper end, what else is this than a life that flows on tranquil and serene? And if thy reading secures thee not serenity, what profits it? Nay, but it doth secure it, quoth he, and that is why I repine at being deprived of it. And what serenity is this that lies at the mercy of every passer-by? I say not at the mercy of the emperor or emperor's favorite, but such as trembles at a raven's croak, and piper's din, a fever's touch, or a thousand things of like sort, whereas the life serene has no more certain mark than this, that it ever moves with constant, unimpeded flow. 145. If thou hast put malice and evil speaking from thee altogether or in some degree, if thou hast put away from thee rashness, foulness of tongue, intemperance, sluggishness, if thou art not moved by what once moved thee, or in like manner as thou once were't moved, then thou mayest celebrate a daily festival, to-day, because thou hast done well in this manner, to-morrow in that. How much greater cause is here for offering sacrifice than if a man should become consul or prefect? 146. These things hast thou from thyself and from the gods. Only remember who it is that giveth them, to whom and for what purpose they were given. Feeding thy soul on thoughts like these, dost thou debate in what place happiness awaits thee, in what place thou shalt do God's pleasure, are not the God's nigh unto all places alike, see they not alike what everywhere comes to pass? 147. To each man God hath granted this inward freedom. These are the principles that in a house create love in a city concord among nations peace, teaching a man gratitude toward God and cheerful confidence wherever he may be in dealing with outward things that he knows are neither his nor worth striving after. 148. If you seek truth you will not seek to gain a victory by every possible means, and when you have found truth you need not fear being defeated. 149. What foolish talk is this? How can I any longer lay claim to write principles if I am not content with being what I am, but am all a flutter about what I am supposed to be? 150. God hath made all things in the world, nay, the world itself, free from hindrance and perfect, and its parts for the use of the whole. No other creature is capable of comprehending his administration thereof, but the reasonable being man possesses faculties for the consideration of all these things. Not only that he is himself a part, but what part he is, and how it is meat that the parts should give place to the whole. Nor is this all. Being naturally constituted noble, magnanimous, and free, he sees that the things which surround him are of two kinds. Some are free from hindrance and in the power of the will. Others are subject to hindrance and depend on the will of other men. If then he place his own good, his own best interest, only in that which is free from hindrance and in his power, he will be free, tranquil, happy, unharmed, noble-hearted, and pious, giving thanks to all things unto God, finding fault with nothing that comes to pass, laying no charge against anything. Whereas if he places his good in outward things, depending not on the will, he must perforce be subject to hindrance and restraint, the slave of those that have power over the things he desires and fears. He must perforce be impious, as deeming himself injured at the hands of God. He must be unjust, as ever prone to claim more than his due. He must perforce be of a mean and abject spirit. 151 Whom then shall I fear? The lords of the bed-chamber, lest they should shut me out? If they find me desirous of entering in, let them shut me out if they will. And why comest thou to the door? Because I think it meet and write, so long as the play lasts, to take part therein. In what sense art thou then shut out? Because, unless I am admitted, it is not my will to enter. On the contrary, my will is simply that which comes to pass. For I esteem what God wills better than what I will. To him will I cleave as his minister and attendant, having the same movements, the same desires, in a word the same will as he. There is no such thing as being shut out for me, but only for them that would force their way in. 152 But what says Socrates? One man finds pleasure in improving his land, another his horses. My pleasure lies in seeing that I myself grow better day by day. 153 The dress is suited to the craft. The craftsman takes his name from the craft, not from the dress. For this reason Euphrates was right in saying, I long endeavoured to conceal my following the philosophic life, and this profited me much. In the first place I knew that what I did are right. I did not, for the sake of lookers on, but for my own. I ate a right unto myself. I kept the even tenor of my walk, my glance composed and serene, all unto myself and unto God. Then as I fought alone I was alone in peril. If I did anything amiss or shameful, the cause of philosophy was not in me endangered, nor did I wrong the multitude by transgressing as a professed philosopher, wherefore those that knew not my purpose marveled how it came about, that will stall my life in conversation was passed with philosophers without exception, I was yet none myself. And what harm that the philosopher should be known by his acts instead of mere outward signs and symbols? 154 First study to conceal what thou art. Seek wisdom a little while unto thyself. Thus grows the fruit. First the seed must be buried in the earth for a little space. There it must be hid and slowly grow, that it may reach maturity. But if it produce the ear before the jointed stalk it is imperfect, a thing from the garden of Adonis. Such a sorry growth art thou. Thou hast blossomed too soon, the winter cold will wither thee away. 155 First of all, I know that I have condemned the life thou art now leading. But when thou hast condemned it, do not despair of thyself, be not like them of mean spirit, who once they have yielded abandon themselves entirely and as it were allow the torrent to sweep them away. No, learn what the wrestling masters do. Has the boy fallen? Rise, they say, wrestle again, till thy strength come to thee. Even thus should it be with thee. For know that there is nothing more tractable than the human soul. It needs but to will and the thing is done. The soul is set upon the right path. As on the contrary it needs but to nod over the task and all is lost. For ruin and recovery alike are from within. 156 It is the critical moment that shows the man. So when the crisis is upon you, remember that God, like a trainer of wrestlers, has matched you with a rough and stalwart antagonist. To what end, you ask? That you may prove the victor at the great gains. Yet without toil and sweat this may not be. 157 If thou wouldst make progress, be content to seem foolish and void of understanding with respect to outward things. Care not to be thought to know anything. If any should make account of thee, distrust thyself. 158 Remember that in life thou shouldst order thy conduct as at a banquet. Has any dish that is being served reached thee? Stretch forth thy hand and help thyself modestly. Doth it pass thee by? Seek not to detain it? Has it not yet come? Send not forth thy desire to meet it, but wait until it reaches thee. Deal thus with children, thus with wife, thus with office, thus with wealth, and one day thou wilt be meet to share the banquets of the gods. But if thou dost not so much as touch that which is placed before thee, but despisest it, then shall thou not only share the banquets of the gods, but their empire also. 159 Remember that thou art an actor in a play, and of such sort as the author chooses, whether long or short. If it be his good pleasure to assign thee the part of a beggar, a ruler, or a simple citizen, then it is to play it fitly. For thy business is to act the part assigned thee well, to choose it is another's. 160 Keep death in exile daily before thine eyes, with all else that men deem terrible, but more especially death, then wilt thou never think a mean thought, nor covet anything beyond measure. 161 As a mark is not set in order to be missed, so neither is such a thing as natural evil produced in the world. 162 Piety toward the gods, to be sure, consists chiefly in thinking rightly concerning them, that they are, and that they govern the universe with goodness and justice, and that thou thyself art appointed to obey them, and to submit under all circumstances that arise, acquiescing cheerfully in whatever may happen, sure it is brought to pass and accomplished by the most perfect understanding. Thus thou wilt never find fault with the gods, nor charge them with neglecting thee. 163 Lose no time in setting before you a certain stamp of character and behavior, both when by yourself and in company with others. Let silence be your general rule, or say only what is necessary and in few words. We shall, however, when occasion demands, enter into discourse sparingly, avoiding common topics as gladiators, horse races, athletes, and the perpetual talk about food and drink. Above all, avoid speaking of persons, either in way of praise or blame, or comparison. If you can, win over the conversation of your company to what it should be by your own, but if you find yourself cut off without escape among strangers and aliens, be silent. 164 Laughter should not be much, nor frequent, nor unrestrained. 165 Refuse altogether to take an oath if you can, if not, as far as may be. 166 Banquets of the unlearned, and of them that are without avoid, but if you have occasion to take part in them, let not your attention be relaxed for a moment lest you slip after all into evil ways, for you may rest assured that, be a man ever so pure himself, he cannot escape defilement if his associates are impure. 167 Take what relates to the body as far as the bear use warrants, as meat, drink, raiment, house, and servants, but all that makes for show and luxury reject. 168 If you are told that such a one speaks ill of you, make no defence against what was said but answer. He surely knew not my other faults, else he would not have mentioned these only. 169 When you visit any of those in power, bethink yourself that you will not find him in, that you may not be admitted, that the door may be shut in your face, that he may not concern himself about you. If with all this it is your duty to go, bear what happens, and never say to yourself, it was not worth the trouble, for that would smack of the foolish and unlearned who suffer outward things to touch them. 170 In company avoid frequent and undue talk about your own actions and dangers. However pleasant it may be to you to enlarge upon the risks you have run, others may not find such pleasure in listening to your adventures. Avoid provoking laughter also. It is a habit from which one easily slides into the ways of the foolish, and apt to diminish the respect which your neighbours feel for you. To border on coarse talk is also dangerous. On such occasions, if a convenient opportunity offer, rebuke the speaker, if not, at least by relapsing into silence, colouring and looking annoyed, show that you are displeased with the subject. 171 When you have decided that a thing ought to be done, and are doing it, never shun being seen doing it. Even though the multitude should be likely to judge the matter amiss, for if you are not acting rightly, shun the act itself, if rightly, however, why fear misplaced censure? 172 It stamps a man of mean capacity to spend much time on the things of the body, as to be long over bodily exercises, long over eating, long over drinking, long over other bodily functions. Rather should these things take the second place, while all your care is directed to the understanding. 173 Everything has two handles, one by which it may be borne, the other by which it may not. If your brothers sin against you, may not hold of it by the handle of injustice, for by that it may not be borne, but rather by this, that he is your brother, the comrade of your youth, and thus you will lay hold on it, so that it may be borne. 174 Never call yourself a philosopher, nor talk much among the unlearned about principles, but do that which follows from them. Thus at a banquet, do not discuss how people ought to eat, but eat as you ought. Remember that Socrates thus entirely avoided ostentation. Men would come to him desiring to be recommended to philosophers, and he would conduct them thither himself. So well did he bear being overlooked. Accordingly, if any talk concerning principles should arise among the unlearned, be you for the most part silent, for you run great risk of spewing up what you have ill-digested. And when a man tells you that you know nothing, and you are not meddled at it, then you may be sure that you have begun the work. 175 When you have brought yourself to supply the needs of the body at small cost, do not peek yourself on that, nor if you drink only water, keep saying on each occasion, I drink water, and if you ever want to practice endurance and toll, do so unto yourself, and not unto others. Do not embrace statues. 186 Section 8 of the Golden Sayings of Epictetus by Epictetus. This is a LibriVox recording. All LibriVox recordings are in the public domain. For more information or to volunteer, please visit LibriVox.org. The Golden Sayings of Epictetus by Epictetus. Translated by Hastings Crossley. Aphorisms 176 through 188, and Appendixes A and B. Aphorism 176 When a man prides himself on being able to understand and interpret the writings of Crispus, say to yourself, if Crispus had not written obscurely, this fellow would have had nothing to be proud of, but what is it that I desire? To understand nature and to follow her. Accordingly, I ask who is the interpreter? On hearing that it is Crispus, I go to him. But it seems I do not understand what he wrote, so I seek one to interpret that. So far there is nothing to pride myself on, but when I have found my interpreter, what remains is to put into practice his instructions. This itself is the only thing to be proud of. But if I admire the interpretation and that alone, what else have I turned out but a mere commentator, instead of a lover of wisdom? Except, indeed, that I happen to be interpreting Crispus instead of Homer. So when anyone says to me, Prithee, read me Crispus, I am more inclined to blush when I cannot show my deeds to be in harmony and accordance with his sayings. Ephorism 1.77 At feasts remember that you are entertaining two guests, body and soul. What you give to the body you presently lose. What you give to the soul you keep forever. Ephorism 1.78 At meals see to it that those who serve be not more in number than those who are served. It is absurd for a crowd of persons to be dancing attendants on half a dozen chairs. Ephorism 1.79 It is best to share with your attendance what is going forward, both in the labor of preparation and in the enjoyment of the feast itself. If such a thing be difficult at the time, recollect that you who are not weary are being served by those who are, you who are eating and drinking by those who do neither, you who are talking by those who are silent, you who are at ease by those who are under constraint. Thus no sudden wrath will betray you into unreasonable conduct, nor will you behave harshly by irritating another. Ephorism 1.80 When Xanthope was chiding Socrates for making scanty preparation for entertaining his friends, he answered, If they are friends of ours, they will not care for that. If they are not, we shall care nothing for them. Ephorism 1.81 Asked who is the rich man, Epictetus replied, He who is content. Ephorism 1.82 Favarenus tells us how Epictetus would also say that there were two faults far graver and fowler than any others, inability to bear and inability to forebear. When we neither patiently bear the blows that must be born, nor abstain from the things and the pleasures we ought to abstain from. So he went on, If a man will only have these two words at heart and heed them carefully by ruling and watching over himself, he will for the most part fall into no sin, and his life will be tranquil and serene. He meant the words bear and forebear. Ephorism 1.83 On all occasions these thoughts should be at hand. Lead me, O God, and thou, O destiny, be what it may the goal appointed me. Bravely I'll follow, nay, and if I would not, I'd prove a coward yet must follow still. Again, who to necessity doth bow a right is learned in wisdom and the things of God? Once more, Critto, if this be God's will, so let it be, as for me, Anatus and Meletus can indeed put me to death, but injure me never. Ephorism 1.84 We shall then be like Socrates, when we can indict hymns of praise to the gods in prison. Ephorism 1.85 It is hard to combine and unite these two qualities, the carefulness of one who is affected by circumstances and the intrepidity of one who heeds them not. But it is not impossible, else were happiness also impossible. We should act as we do in seafaring. What can I do? Choose the master, the crew, the day, the opportunity. Then comes a sudden storm. What matters it to me? My part has been fully done. The matter is in the hands of another, the master of the ship. The ship is foundering. What then have I to do? I do the only thing that remains to me, to be drowned without fear, without a cry, without upbraiding God, but knowing that what has been born must likewise perish. For I am not eternity, but a human being, a part of the whole, as an hour is part of the day. I must come like the hour, and like the hour, must pass. Ephorism 1.86 And now we are sending you to Rome to spy out the land.   We have but aired and sending such a spy as you. Diogenes, who was sent as a spy long before you, brought us back another report than this. He says that death is no evil, for it need not even bring shame with it. He says that fame is but the empty noise of madmen. And what report did this spy bring us of pain? What of pleasure? What of want? That to be clothed in sackcloth is better than any purple robe. That sleeping on the bare ground is the softest couch. And in proof of each assertion, he points to his own courage, constancy, and freedom, to his own healthy and muscular frame. There is no enemy near, he cries, all is perfect peace. Aphorism 187. If a man has this peace, not the peace proclaimed by Caesar, how indeed should he have it to proclaim? Nay, but the peace proclaimed by God, through reason, will not that suffice him when alone, when he beholds and reflects. Now can no evil happen unto me. For me there is no robber, for me no earthquake.  Neither highway, nor city, nor gathering of men, neither neighbor nor comrade, can do me hurt. Another supplies my food, whose care it is. Another my raiment. Another hath given me perceptions of sense and primary conceptions. And when he supplies my necessities no more, it is that he is sounding the retreat, that he hath opened the door, and is saying to thee, Come, wither, to not that thou needest fear, but to thy friendly kindred elements, whence thou didst spring. Whatsoever of fire is in thee, unto fire shall return. Whatsoever of earth, unto earth, of spirit, unto spirit, of water, unto water. There is no Hades, no fabled river of size, of lamentation, or of fire.  With thoughts like these, beholding the sun, moon, and stars, enjoying earth and sea, a man is neither helpless nor alone. Aphorism 188. What wouldst thou be found doing when overtaken by death? If I might choose, I would be found doing some deed of true humanity, of wide import, beneficent and noble. But if I may not be found engaged in ought so lofty, let me hope for at least this, what none may hinder, and what is surely in my power, that I may be found raising up in myself that which had fallen, learning to deal more wisely with the things of sense, working out my own tranquillity, and thus rendering that which is its due to every relation of life. If death surprise me thus employed, it is enough if I can stretch forth my hands to God and say, The faculties which I received at thy hands for apprehending this thine administration I have not neglected. As far as in me lay I have done thee no dishonor, behold how I have used the senses, the primary conceptions which thou scavest me. Have I ever laid anything to thy charge? Have I ever murmured at ought that came to pass, or wished it otherwise? Have I in anything transgressed the relations of life? For that thou didst beget me. I think thee for that thou hast given, for the time during which I have used the things that were thine it suffices me. Take them back, and place them wherever thou wilt. They were all thine, and thou gaveest them me. If a man depart thus minded, is it not enough? What life is fairer and more noble, what end happier than his. A. Fragments attributed to Epictetus. Fragment 1. A life entangled with fortune is like a torrent. It is turbulent and muddy, hard to pass and masterful of mood, noisy, and of brief continuance. Fragment 2. The soul that companies with virtue is like an ever-flowing source. It is a pure, clear, and wholesome draught, sweet, rich, and generous of its store. That injures not, neither destroys. Fragment 3. It is a shame that one who sweetens his drink with the gifts of the be, should embitter God's gift reason with vice. Fragment 4. Crows pick out the eyes of the dead, when the dead have no longer need of them, but flatterers may mar the soul of the living, and her eyes they blind. Fragment 5. Keep neither a blunt knife nor an ill-disciplined looseness of tongue. Fragment 6. Nature hath given men one tongue but two ears, that we may hear from others twice as much as we speak. Fragment 7. Do not give sentence in another tribunal, till you have been yourself judged in the tribunal of justice. Fragment 8. It is shameful, for a judge to be judged by others. Fragment 9. Give me by all means the shorter and nobler life, instead of one that is longer, but of less account. Fragment 10.  Fragment 11. Of pleasures, those which occur most rarely give the most delight. Fragment 12. Exceed do measure, and the most delightful things become the least delightful. Fragment 13. The anger of an ape, the threat of a flatterer, these deserve equal regard. Fragment 14. Chastise thy passions, that they avenge not themselves upon me. Fragment 15. No man is free who is not master of himself. Fragment 16. A ship should not ride on a single anchor, nor life on a single hope. Fragment 17. Fortify thyself with contentment, that is an impregnable stronghold. Fragment 18. No man who is a lover of money, a pleasure, of glory, is likewise a lover of men. But only he that is a lover of whatsoever things are fair and good. Fragment 19. Think of God more often than thou breathest. Fragment 20. Choose the life that is noblest, for custom can make it sweet to thee. Fragment 21. Let thy speech of God be renewed day by day. I rather than thy meat and drink. Fragment 22. Even as the sun doth not wait for prayers and incantations to rise, but shines forth and is welcomed by all, so thou also wait, not for clapping of hands and shouts and prays to do thy duty, nay, do good of thine own accord, and thou wilt be loved like the sun. Fragment 23. Let no man think that he is loved by any who loveth none. Fragment 24. If thou rememberest that God standeth by to behold and visit all that thou dost, whether in the body or in the soul, thou surely will not err in any prayer or deed, and thou shalt have God to dwell with thee. Shwegghauser's Great Edition collects 181 fragments attributed to Epictetus, of which but a few are certainly genuine. Some, as 21 and 24 above, bear the stamp of Pythagorean origin. Others, though changed in form, may well be based upon Epictetian sayings. Most have been preserved in the anthology of John of Stibai, or Stibias, a Byzantine collector, of whom scarcely anything is known but that he probably wrote toward the end of the fifth century, and made his vast body of extracts from more than 500 authors for his son's use. The best examination of the authenticity of the fragments is Questionis Epictidae by R. Asmus, 1888. The above selection includes some of doubtful origin, but intrinsic interest. Crossley. Appendix B. The hymn of Cleanties. Chiefest glory of deathless gods, almighty for ever, sovereign of nature that rulest by law. What name shall we give thee? Blessed be thou, for on thee should call all things that are mortal. For that we are thine offspring. Nay, all that in myriad motion lives for its day on the earth bears one in press thy likeness upon it. Wherefore my song is of thee, and I hymn thy power for ever. Lo, the vast orb of the world's rounder the earth ever more as it rolleth, feels thee its ruler and guide, and owns thy lordship rejoicing. I, for thy conquering hands, have a servant of living fire, sharp is the bolt, where it falls, nature shrinks at the shock, and doth shudder. Thus thou directest the word universal, that pulses through all things, mingling its life with lights that are great and lights that are lesser, ian as besiemit its birth, high king through ages unending. Not is done that is done without thee in the earth or the waters, or in the heights of heaven save the deed of the fool and the sinner. Thou canst make rough things smooth, at thy voice low, jarring disorder moveth to music, and love is born where hatred abounded. Thus hast thou fitted alike things good in things evil together, that over all might reign one reason supreme and eternal. Though there unto the hearts of the wicked be hardened and heedless, woe unto them! For while ever their hands are grasping at good things, blind are their eyes, yea, stopped are their ears to God's law universal. Calling through wise disobedience to live the life that is noble, this they mark not, but heedless of right turn each to his own way, here a heart fired with ambition, in strife and straining unhallowed. There thrusting honor aside, fast set upon getting and gaining. Others again given over to lusts and disillute softness, working never God's law, but that which weareth upon it. Nay, but, O giver of all things good, whose home is the dark cloud, thou that wields heaven's bolt, save men from their ignorance grievous. Consider its night from their souls, and grant them to come to that wisdom, wherewith all sistered with justice, thou rulest and governest all things, that we honored by thee may requite thee with worship and honor, evermore praising thy works, as is meat for men that shall perish. Seeing that none, be he mortal or God hath privilege nobler, and without stint, without stay, to extol thy law universal. End of the Golden Sayings of Epictetus by Epictetus. Translated by Hastings Crossley. Recording by Doug Wetzel.


Welcome to Learning English, a daily 30-minute program from the Voice of America. I'm Ashley Thompson. And I'm Dan Novak. This program is designed for English learners, so we speak a little slower, and we use words and phrases, especially written for people learning English. Coming up on the program, Gina Bennett reports on how birds in North America will no longer be named after people. Gregory Stockle has a story on Colombia's efforts to control invasive hippos. Katie Weaver has this week's health and lifestyle report on a possible cure for sickle-cell disease. Later, Jill Robbins and Andrew Smith present the lesson of the day, but first, Birds in North America will no longer be named after people. The American Ornithological Society announced the move Wednesday. Next year, the organization will begin to rename around 80 birds found in the United States and Canada. Colleen Handel is the organization's president. She said, there is power in a name, and some English bird names have associations with the past that continue to be exclusionary and harmful today. Everyone who loves and cares about birds should be able to enjoy and study them freely, Handel added. Rather than review each bird named after a person individually, all birds named after people will be renamed, the organization announced. Birds that will be renamed include those currently called Wilson's Warbler and Wilson's Snipe. Those are both named after the 19th century naturalist Alexander Wilson. Audubon's Shearwater, a seabird named for John James Audubon, also will get a new name. In 2020, the organization renamed a bird that used to be named after Confederate Army General John P. McCown. It is now called the Thick-Build Longspur. I'm really happy and excited about the announcement, said Emily Williams. She is an ornithologist at Georgetown University in Washington, D.C., who was not involved in the decision. She said debates over bird names have been happening among bird watchers for the past several years. Naming birds based on habitat or appearance is one of the least problematic approaches, Williams said. Earlier this year, the National Audubon Society announced that it would keep its name. Some critics argued that the group should lose its connection to John James Audubon, whose family owned slaves. The name has come to represent so much more than the work of one person, Susan Bell told Audubon Magazine in March. She is chair of the National Audubon Society's Board of Directors. Bell added, we must reckon with the racist legacy of John James Audubon. A 2020 incident in New York's Central Park has been reported as an example of discrimination that black people sometimes face when trying to enjoy the outdoors. Christian Cooper, a black bird watcher, was looking for birds when he asked a white woman, Amy Cooper, to follow local rules and leash her dog. Cooper called the police and was later charged with filing a false police report. Police later dropped the charge. Soon after, a group of bird watchers organized the first Black Birders Week for black nature lovers and scientists. I'm Gina Bennett. Colombia will try to control its population of more than 100 hippopotamuses, large animals from Africa. The South American country aims to control the big animals using several methods. Animals might sterilize the animals through a medical operation. They might move the hippos to other countries or possibly euthanize them, the government said recently. The animals' ancestors were brought to the country by the late Pablo Escobar in the 1980s. Escobar was the leader of an illegal drug operation in Colombia. The hippos have spread from Escobar's home to nearby rivers where they have reproduced. They have no natural predators in Colombia and the government has declared them as an invasive animal that could hurt the environment. Animals estimate there are 169 hippos in Colombia and that many of them are in the Magdalena River area. They estimate that if no measures are taken, there could be 1,000 by 2035. President-Minister Susana Muhammad said the first step of the plan will be to sterilize 40 hippos each year and this will begin soon. The method is costly. Each sterilization costs about $9,800 and there are risks for the hippos including reactions to medicines or death, as well as risks to health officials, the ministry said. The hippos live across a large area. They are territorial and aggressive. Experts say sterilization alone is not enough to control the growth of the invasive animals. The government announced in March that it is planning to possibly move the animals to other countries. Muhammad said Colombian officials have contacted officials in Mexico, India, and the Philippines. And they are considering a plan to send 60 hippos to India. We are working on the protocol for the export of the animals, she said. We are not going to export a single animal if there is no authorization from the environmental authority of the other country. As a last means to control the population, the ministry is creating a protocol to euthanize the animals. A group of hippos was brought in the 1980s to Hacienda, Nepalese. The place was Escobar's private zoo. Now it receives many visitors after his death in 1993. Most of the animals live freely in rivers there and reproduce without control. I'm Gregory Stockle. A group of health experts recently announced that a new gene editing treatment for sickle cell disease was safe for patients. The treatment could provide a new cure that attacks the disease at its genetic source. Sickle cell disease, SCD, is a genetic blood disorder that affects millions of people worldwide. The disease is common in places with high cases of malaria, like Africa and India. It strikes among black Americans, Africans, and Middle Easterners more often than other groups. Scientists believe being a carrier of SCD helps protect against severe malaria. People with SCD carry unhealthy blood cells that result in blockages called blood clots. This can cause pain and damage bones and organs in the human body. The World Health Organization said many children with the most severe form of the disease die before the age of five, usually from an infection or severe blood loss. Vortex pharmaceuticals and CRISPR therapeutics make the new treatment called XSL. The treatment involves permanently changing the genetic material, DNA, in a patient's blood cells. The goal is to help the body return to healthy blood cell production. Healthy blood cells are present at birth, but abnormal cells begin to develop in people with sickle cell disease. When patients receive the treatment, stem cells are removed from their blood, and the gene editing tool, CRISPR, is used to remove the switching gene.  Vortex reported 46 people got the treatment in its study. Among 30 of them who had at least 18 months of observation, 29 were free of pain crises for at least a year. All 30, Vortex reported, avoided being hospitalized for pain crises for that long. Victoria Gray of Mississippi was the first patient to test the XSL treatment. Gray told researchers at a scientific gathering earlier this year that she had suffered from pain since childhood. She described feeling reborn the day she got the treatment. My children no longer have a fear of losing their mom to sickle cell disease, she said. The U.S. Food and Drug Administration, FDA, had already found the treatment effective in a study of SCD patients. The health agency, however, was not sure if the small genetic sample size used in the study captured the entire U.S. population for sickle cell disease. With the expert's findings, the FDA is likely to approve the treatment in early December for patients aged 12 and older. If the treatment is approved, Vortex has also proposed to follow up with patients to study its safety for another 15 years. Vortex has not said how much the treatment will cost. But the Institute for Clinical and Economic Review estimates the cost could be around $2 million for the treatment. By comparison, research earlier this year showed medical costs for sickle cell treatments from birth to age 65 could add up to $1.7 million. Dr. Allison King of Washington University School of Medicine in St. Louis, Missouri cares for children and young adults with sickle cell disease. She told the Associated Press that the new treatments would be costly. But if you think about it, she said, how much is it worth for someone to feel better and not be in pain and not be in the hospital all the time? I'm Katie Weaver. You just heard today's Health and Lifestyle Report. Katie Weaver joins me now to talk more about the story. Welcome back, Katie. Hi, Dan. Nice to see you. Katie, you reported on a possible cure for sickle cell disease. Can you tell me a little more about the condition? Our listeners might not know the word sickle. What does it mean? Well, SCD is a genetic condition that deforms red blood cells. It is also called sickle cell anemia. The red blood cells of a person with SCD become sticky and harden into an unusual shape like that of a sickle, a hand tool with a sharp rounded edge used to cut grasses and other plants. The pain from sickle cell disease is intense. How have doctors traditionally treated the sickness? Current treatments include medications and blood transfusions. The only permanent solution is a bone marrow transplant, which must come from a closely matched donor without the disease and brings a risk of rejection. But this new treatment in your report requires no donors. That's right. It uses the patient's own genetic material. That is a big step forward because there is little risk of rejection. Well, let's hope this new treatment can bring about a cure. Thanks for coming on the show, Katie. You bet. I enjoyed it, Dan. My name is Anna Matteo. My name is Andrew Smith. And I'm Jill Robbins. You're listening to The Lesson of the Day on the Learning English podcast. Welcome to the part of the show where we help you do more with our series, Let's Learn English. The series shows Anna Matteo in her work and life in Washington, D.C. On The Lesson of the Day, we like to help you learn from even small amounts of the language you hear in the Let's Learn English series. Sometimes you can learn a lot from just a little. Listen now to the beginning of Lesson 32 of the series. See if you can notice little expressions Anna uses. First to show excitement and then to show that she is worried. Hello. Today is a big day. My first children's show is on television. Woohoo! I'm excited and nervous. Hello, Anna. Hello, Ms. Weaver. Some people are going to watch your children's show. After they watch it, they'll tell me what they liked and what they didn't like. Oh dear. Oh dear is what we call an interjection. Those are words, sounds, or phrases we use to quickly show feelings. Oh dear shows that Anna is worried about whether people will like her new children's show. Ms. Weaver also looks very serious in the video, so I think Anna is worried about that too. But what interjection did Anna use to show her excitement? Hello. Today is a big day. My first children's show is on television. Woohoo! I'm excited. Woohoo is right. When we get good news or are excited about something, we sometimes use this interjection. It's not really a word, it's more just like a sound. It's an interjection. Interjection. Interjection. Interjection. Interjection. Interjection. And what other interjection does Anna often say to show she is excited? Here's a hint. It begins with the AW sound. And it is also a real word in English. And the interjection is? Americans say this expression a lot, but our listeners might be curious to know what other meaning the word has. Awesome is an adjective. And the noun form of the word is AW, spelled A-W-E. To feel AW is to feel very amazed or even frightened or fearful when you see or experience something big or special. For example, if you are looking at a huge mountain or the world's tallest building or a natural wonder such as the Grand Canyon in the United States, you might have the feeling of AW. And so you would say that the mountain or building is an awesome sight or an awesome thing to behold. Behold is sort of a fancy word that just means to see or look at. Jill, Anna said, oh dear, because she suddenly felt worried. What are some other polite interjections we use when we are disappointed, upset or worried? We say uh-oh if we think something is wrong, like if we've made a mistake or a machine is broken and if we get bad news or a bad result, we can say polite interjections like darn, rats, shucks, or shoot. That's right, believe it or not, we sometimes make mistakes when we are doing this podcast and we might say something like that. For another example, if you are playing a sport and you make a bad mistake, you might say rats. Of course, native speakers also say curse words, or words that are not polite, has interjections to express negative feelings such as frustration, anger, or disappointment. But we'll let our listeners find those on their own. You're darn right, we will. I'm Jill Robbins and you're listening to the Lesson of the Day on the Learning English Podcast. Now let's go back to the beginning of Lesson 32. Listen to Ms. Weaver again. Some people are going to watch your children's show. After they watch it, they'll tell me what they liked and what they didn't like. Here's a bit of grammar for our listeners. In her second sentence, Ms. Weaver uses what we call a noun clause as the direct object of the verb tell. After they watch it, they'll tell me what they liked and what they didn't like. The noun clause is the words what they liked. A clause has a subject and a verb. The subject is the pronoun they and the verb is liked. Together, the words what they liked act just like a noun because they are the object of the verb tell. They'll tell me what they liked. One mistake people learning English make is they will say what did they like in this situation because the word what makes it seem like a question. But it's not a question. It's just a noun object of the verb. That's right. Like if I say tell me the answer, the word answer is the object. So the noun clause works the same way. I can say tell me what you think. What you think is the object. But what about the pronoun me in the sentence tell me what you think? That is called the indirect object. It's like saying tell what you think to me. But in English, we usually put the pronoun before the direct object. We can hear more examples of the indirect object in lesson 32. Listen as Anna explains the special machine she will use in her children's show. Hello, I'm Anna. Welcome to the Time Traveling Treehouse. This is not a usual treehouse. It can time travel. That's why it's called the Time Traveling Treehouse. Anna, do not forget me. Of course not. This is my partner, Mindy. My name means massive information navigation device for you. That means we can travel to many places and learn many things. Kids from all over the world ask us questions. We find them answers. Woohoo! That is right, Anna. Mindy, what is our first question? Laila asks us this question. We hope you heard the interjection that the machine named Mindy used. And the examples with pronouns as indirect objects placed before the direct object were these. Kids from all over the world ask us questions. We find them answers. And Laila asks us this question. On our website at learningenglishatvoanews.com you can download for free the lesson plan that goes with lesson 32 of Let's Learn English. It explains direct and indirect objects and many other things about lesson 32. And now here's a little poem that uses many indirect objects. You gave me your hand and opened your heart. You gave us a chance to make a new start. I'll tell you my hopes. I'll tell you my dreams. I'll give you my love and all that it means. Like rivers that run from hills to the sea, we'll flow day by day together and free. I offer my words. I open my door. The day you walk in, I need nothing more. Oh that's really sweet Andrew. I hope your girlfriend likes it when you find her. I hope she does too. And remember that you can ask us questions by writing us at learningenglishatvoanews.com. You could also find us on YouTube, Facebook and Instagram. Thanks for listening to the Lesson of the Day on the Learning English Podcast. I'm Jill Robbins. And I'm Andrew Smith. And that's our program for today. Join us again tomorrow to keep learning English through stories from around the world. I'm Ashley Thompson. And I'm Dan Novak.


Jack, I got a couple for you, wait for Megan. Just sort of great first half and then they make that big run in the third quarter, just what you see there. Yeah, that was the message after the game is being able to sustain it. I think we were up 10 at half. Might have been, we could have had six more points just because we were able to turn them over. We didn't convert on some of those turnovers. So being able to capitalize when we have the opportunity, maybe that league is 16 or 18 at half, but the ability to sustain. 66 points for them in the second half. They got to the rim. We got to be able to sustain it. And then you mentioned the turnovers.  Just how much of that on your end was obviously got length, true, honest, talked about the newness. How much of those do you think were self-inflicted versus the way they defend? Excuse me. Yeah, I think overall for us to be able to force a turnover, which is great, means we were in the right place and being active ourselves. I think some of ours were unforced and that's the part that we got to capitalize on. I said that to the group is making sure we take advantage of each possession. And if you need to hit a single instead of a home run, a single is a lot of times pretty good. Coach, there were times where Yanis just got downhill and got what he wanted. What can you do with that? Yeah, we were good at some areas where we had two bodies on him and he was still able to convert early in the first half and really took it up a notch in the third quarter and made a difference. You can elect to foul him, try to at the rim, put him on the ground. You can do some strategies. We tried to put two bodies around him. Pretty impressive by him still finishing at the rim. Are you able to take any positives from this game, given how you guys performed the first three quarters before he started to do this? Yeah, for sure. I love how our group was on the bench, first of all, the communication. I think we were locked into the game plan. Our approach at the beginning of the game was really good, gave ourselves a chance at halftime. And I think overall it's a message for us to be able to sustain this thing and be able to do it in the third quarter and fourth quarter against a lead team. When we're not shooting well, I think we went four for 19. There was a stretcher from three. So the difference was they got to the rim and we shot some mid-range at that time. And so that conversion rate is definitely in their favor. Your starters logged a lot of minutes in the first half.  And do you think that played a role in the second half? Guys wearing down, or was that just an MVP player playing like an MVP? Yeah, I think you see the last two games, the minutes have been increasing with that start in five. And I think overall that will continue. You know, when I came back from the break, I told our group there's 24 games that we had left. We're going to take each game extremely serious and try to win each game. So I wasn't really concerned about this being a back-to-back. Played those guys heavy minutes to try to give ourselves a chance in the first half, but you give them a walk and credit for responding. Jack, you guys had, I think, nine assists on your first 10 baskets. I think it stayed pretty consistent for a bit. Do you think there was any drop-off in the ball movement and the way you guys were spraying around in the first half and how much of that was getting kind of the offense, getting stagged in versus, you know, maybe some adjustments they might have made? I think they did make some adjustments as far as going smaller a little bit. So that helped them. They ended up switching a little bit. That helped them. So they were able to keep us in front a little bit. But the shots that we got, there was a stretch where I thought every ball was going in, looked good from multiple people. So not really concerned about that piece. So I thought overall, I remember a time I was saying, the process is extremely correct. Like, keep doing it. You're getting your teammates good looks. We just got to make them. Jack, you mentioned that process. And before, during pregame, you talked about how playing fast was going to be a main point of emphasis that you guys did in Atlanta. For tonight, what did you see from the group that allowed you guys to start off with that fast pace? That's going to be important as you guys kind of move forward and grow. Yeah, and Megan, that was another message to the team after the game is, it takes an extreme condition level to be able to play that pace and to play hard on the defensive end of the floor.  Make sure you're maintaining it, being in shape. So we can play fast. I thought overall, we wanted to get out before that defense was set. We did so a lot of times. We just got to take advantage and transition. Coach, Mikhail 31, I know you've spoken about wanting to get out, shoot a lot of threes and get to the rim, but his ability to create a mid-range, what does that do for you guys? Don't want to live with it, because you play a team like tonight, that's the shot they want to give up. That's their profile defensively. And so if you're making it out of high level, you really get rewarded for it. But you see getting to the rim puts the extreme amount of pressure on your defense. So we can mix in, get into the rim, like they did in the second half, we can take some of that mid-range.


All right, so in this video we are going to cover the second part of detecting outliers in dashboard using validation rule notifications. The way that we're going to do this is by building predictors and then tying those predictors to our validation rule notifications. But in this video we're just going to go over how to configure the predictors. Before we get into the nitty-gritty of building predictors, let's just quickly take a look at some examples of the kinds of outliers that we're going to be able to detect with these predictors and automatic validation notifications. Here is a very common picture that we see in a lot of countries. We see we have various data elements, sometimes indicators, progressing over a series of months as a line chart, and then we see one month for one of these data values that is significantly higher than all of the others. You see most of them have a fairly linear trend and you see this one peak jutting out right in April 2018. This is clearly an outlier. This data does not follow the normal trend. This data is so high above the normal accepted value range that you can clearly see illustrated here that it's almost certainly a data quality mistake. Now these kinds of data quality mistakes can throw off national statistics. So if every month we're expecting about 54,000, in this case BCG doses, and then in one month you report 170,000 BCG doses, now of course that could be from a massive, massive outreach campaign, maybe some door-to-door vaccination efforts, but by and large almost always these are going to be data entry errors where maybe a person at a health facility or a hospital, maybe they meant to put in 7,000 doses given and they put in 70,000 doses given on accident. It's a very easy thing to do.  And so we see a clear example of this here where you see a very common trend across all these various data elements. They're not changing or fluctuating that much, month to month, but one month is really jutting out. And if we were to leave this data entry error in place, then for April 2018 you would probably see that the BCG dose coverage was well over 100%, maybe 200%. And that would make folks question the quality and the validity of all of the other data. If you have one month that's 200% BCG coverage, can we trust the rest of the data? So the point is that it's very, very important to identify and correct these kinds of data entry errors. And the way that we're going to start showing you how to do today is have DHIs to do this for you, have DHIs to automatically detect these kinds of data entry errors, these kind of data quality problems, and send you a notification when it has detected them so that you can correct it immediately. You do not want these kinds of data entry errors to linger in the system for very long. So on this slide, we're going to look at just a couple of other examples of some clear outliers. The chart at the top is looking at BCG doses to measles one doses dropout rate. So that is the proportion of children who are receiving the BCG dose and then not receiving the first measles dose. And we expect this to be zero. We expect them every single BCG dose to be the same value as the measles dose. We expect every person to get both vaccinations. And we can see that in some org units, and these bars here are representing org units, that we have some locations where the children are receiving significantly higher BCG vaccines versus measles vaccines. Now, of course, this is should not be the case. We should always see that the number of BCG vaccines are the same as the number of measles vaccines. This top chart is showing us the BCG to measles one dose dropout rate. And what we expect to see is that the number of BCG doses given is equal to the number of measles doses given. Here on the top chart, we have a target line of zero. Again, that's indicative of the BCG vaccines doses given should equal the measles. We should be a one to one relationship there. Then we're giving ourselves an acceptable maximum range of 20%. And that means that we are allowing in this particular country scenario, a dropout rate of 20% from BCG vaccine to measles one, meaning that 20% of the children who got the BCG vaccine will not get the measles one dose. And they're saying that that's an acceptable range. Of course, not ideal, but an acceptable range. But you see we have two bars here. These bars are representing health facilities where we have a 72.1% dropout rate and a 73.4% dropout rate. Now, what does this mean? This means that we have 72.1 and 73.4% of the children who received the BCG vaccine, not receiving the measles vaccine. Now, obviously, this is a big problem. This is either a data quality mistake, or this is some kind of breakdown in clinical service delivery. We should never see a dropout rate this high. So this is telling this program manager that, hey, we've got problems in these two health facilities, in that the majority of children who are receiving the BCG vaccine are then not receiving the measles. And so I need to follow up. Hopefully, in this scenario, you find that it's a data quality problem. If it's not a data quality problem, then you have some serious problems with your measles one doses in these two health facilities. So those are the bars that are going above the acceptable maximum range. Let's look now, though, at these few bars that are going below the zero target line. So they're going down. These are negative values. And we see that there are two here that are really quite big. We have one that's negative 74.5 and one that's negative 70 or 271.4. What does this mean? This essentially means that we have more children receiving the measles vaccine than we have receiving the BCG vaccine. Now, that is extremely unusual, basically impossible from a clinical perspective. This is almost certainly a data quality issue in these two health facilities where the bar is going lower than the target line. And you see that we actually have three others that health facilities that are reporting that the measles one is higher than the BCG. Now, there should be an acceptable range for this too. We appreciate that in many countries, you're reporting on two different cohorts of children between the BCG vaccine and the measles one vaccine. Maybe you have some kind of seasonal birth patterns or trends in your country. But a value of negative 74.5 and negative 271.4 should be considered extremely unacceptable no matter how much seasonality you have to your birth rates in your country. It's basically guaranteed that these are data quality problems that someone accidentally put in far too few BCG vaccines or far too many measles one doses. So these are definitely something that needs to be followed up on. And the point of this chart at the top here is showing you that you can see these very, very, very clearly these bars that are way too high and these bars that are way too low. And you're going to be able, if you're looking at this, if you're a program manager to immediately follow up on these, they should be as obvious as they possibly can be. Again, examples of outliers, especially that negative 271.4, an extreme outlier. All right, let's take a look at the next chart below this. This next chart below this is looking at new malaria cases under five versus malaria new malaria cases five and above. The under five are showing up here as the green portion of the stacked column, excuse me, this is a stacked bar chart. And the blue portion is showing the five and above proportion of the population in the stacked bar chart. And you see that we have set our range for this chart to be up to 100%. So here we have essentially a clear representation of the proportion of total new malaria cases being disaggregated by under five and over five. Now, we expect in most countries that have malaria to have about 30% of our new malaria cases to be under five. Okay, that's a very, very common trend that we see around the world where we have endemic malaria. So you see that at the 30% line, that's what we have. We have that that a black line going through 30% that says expected range under five minimum. Now, we're giving ourselves a little bit of a buffer because it can vary based upon your population distribution in terms of age, but we then give ourselves an acceptable upper range of 35%. And you see again at the 35% line, we have a strong black line cutting through that. And it's telling us that between 30 and 35%, we should see that under five population end and the over five population begin. Now, what you see here, if you look through the months, kind of going from top to bottom, as you scan through, you see that in November 2018, our new malaria cases under five are around 65%. You see that green at November 2018, you see that green line going way, way, way, way past the acceptable ranges and going far into what in the other months is just the blue, just the over five. And this is another clear indication of an outlier. So November 2018, there is clearly an outlier in your new malaria cases under five. Someone accidentally put in a value that was way too big. And you can see that it's throwing off our national statistics, it's throwing off our national distribution and disaggregation of our age breakdown of the new malaria cases. So if you were to look at this, you would say that somehow in November 2018, 65% of our malaria cases were under five population. Now, that's just not clinically possible. Unless you, I just, I can't even imagine a scenario in which that's clinically possible. So that means that you have an outlier, you have a day equality problem in November 2018. And if you look at the values that we have reported for our new under five cases, most months, they're ranging between, yeah, about 100,000, maybe 150,000, something like that. But here in November 2018, we're up above nearly, we're nearly 300,000 cases. Whereas our over five is still in the acceptable average that we're seeing. And of course, you have to appreciate that malaria is seasonal. So it's going to, what we're not seeing here is the seasonal curve. But we're still seeing that the proportion is way out of whack. It's just not possible. So again, another clear indication of an outlier. The point of these two charts really is to show that we can see outliers in a lot of different ways, right? In the first chart, we saw that we can see an outlier stick up in a kind of month to month trend. Here in the, on the first chart here, we're able to see that outliers being illustrated by a relationship between two different data elements. So for example, here, a BCG to measles one dose dropout rate. So we're comparing these two data elements together to see outliers in one or the other. And then on this malaria example on this bottom chart, we're seeing outliers represented by disaggregations of our clinical data by age. You maybe also can do this by gender. And so these are just to show you that we can find outliers in a lot of ways, but this requires you to look at the dashboards, to look at your charts, to have these, that you're routinely looking at them. Of course, people are not always routinely looking at their DHIS2 dashboards. And so the most effective way to make sure that people address these kinds of outliers that are throwing off natural statistics is to configure DHIS2 to be able to automatically detect it and to send a notification to the user who can correct it. Okay. So let's take just before we get into the crazy predictor stuff, let's just do a quick overview of how do we identify these outliers on a standard dashboard and isolate the actual outlier itself. Well, we have some steps for this. And I'm going to show these to you just in a second. The first step is that we want to isolate the period. They usually, we just want to drill into one month. Then we want to change the chart type to a bar chart. Then we need to isolate the data element. Then we need to isolate the facility level to see where the data is coming from. And then we change the layout so that org units is in category, periods in filter, and data is in series. Now, I just did that really fast. Let me just show it to you in real life here. So I'm going to go to the demo site for the academies. Here we are. I'm going to log in as demo and then district one, hashtag. Yeah. Okay. So here we have a similar chart to what I just showed you. And I think even Bob mentioned this in the videos. Where is the outlier here? Well, there's probably two outliers. This point here back May 2019, A&C first visits, and this one here A&C first visits from January 2020. Now, how do we figure out where this data is coming from? Where's the facility that's causing this outlier? Now we need to do a quick recap of how to use the data visualizer app. So what I'm going to do is just show you the whole process here. I am going to, I can't explore this on the dashboard. So I'm going to click the open in visualizer app button. And that's going to take me into the data visualizer application. So now we're in the application and we can start to drill into this data. What was my first step? My first step was to isolate the periods. So we know that the outlier is in January 2020. I am going to go to my period selection. I'm going to deselect all these periods. You see we have 13 months here selected. I'm going to deselect these. I'm going to go to fixed periods and I'm going to say January 2020. Turn that one on. And here we go. Just some dots because, you know, we have a trend line, but we don't have a trend if it's just one period. Here's still my outlier way up here. Then we need to change the chart type to a bar chart. So I'm going to go over here to the chart types. Change it to a column. You could also change it to bar. I'm going to choose column. And there we go. So now we actually see all the data next to each other. And still here's our outlier. All right. Now we want to isolate that data element. The data element that has the outliers A and C first visits. So I'm going to come to data. And I'm going to turn off everything that's not A and C first visits. Click update. Boom. Now we just got one big bar. That's fine. Now let's figure out where this data is actually coming from. Now the easiest way to do that is to go into our organizational units. And you see right now I have user organization, the relative user organization units tick box selected. I'm going to untick that. I'm going to select national level or the national and then I'm going to select my level and I'm going to go ahead and go all the way down to facility level. Okay. So that's going to show me all of the facilities. Click update. Nothing changed. Why did nothing change? Because my layout is not correct. So the last step is to change the layout. We are going to move organizational units to category. We are going to move period to filter, which automatically went for us when we switched out with the org units. And we're going to leave data in series. Click update. Boom. Where is that outlier? Well, it is clear. This is right here. Outlier is at facility 147. And in one month they reported 35,888 ANC first visits. Okay. This is how you isolate for the outliers going from a dashboard in through the data visualizer. A few steps here, right? You also have to know how to use the data visualizer. Now wouldn't it be nice if this notification was just sent directly to my email? How do we do that? Well, that's what we're going to talk about now. How do we see this outlier sent directly to my email? I know I just went through that quite quickly. If you want to revisit how I just gone through and used the applications in the dashboards to identify this outlier, please go back and rewatch this presentation. And you're certainly welcome to slow it down if necessary. All right. And again, I showed this example just before the break, but Rwanda has at least configured some to do this at least partially to automatically detect the outliers and send them and push them to people's to emails. All right. So the way that we actually calculate the outlier threshold, we have to compare the data that is entered against an outlier threshold. The way that we actually calculate that outlier threshold is using predictors. And we put that predicted value into a validation rule. Predictors have typically only been used for data elements in DHS 2.28 to 2.34. Starting in 235, we can actually start to do some of this analysis, not using predictors, but using indicators. So the release that we actually just put out yesterday, you can start to use this in standard indicators. But most of you, basically all of you, because we released it yesterday, are not using 235 yet. I'm going to show you how to do it in 228 to 2.34. So let's take a look at some of these predictors. Let's take a look at some example predictors. What are these calculations for? So predictors really use previously reported values. They use previously reported values to calculate a new value. That's really what predictors are for. And we can, a couple of examples of this. So the first example, I want to get the average malaria incidence over the last six months. You can't use a standard indicator for that. You cannot use, the only thing that you can use to calculate that value in DHS 2 is a predictor. Another example, I want to calculate the average ART consumption over the last three months. Maybe you're using DHS 2 for some kind of supply chain monitoring. And using predictors, you would be able to calculate, say, average consumption. Next point, I want to see the average ANC visits with three standard deviations. Remember, we talked about what standard deviations were yesterday. For the last 12 months, this would produce an ANC 1 outlier threshold. This is really the actual, we're going to be building now. We want to see what is the outlier threshold. And the way we calculate that is we want three standard deviations from the average over the last 12 months. Predictors can also be used, the next bullet point, the fourth bullet point here. Predictors can also be used to count the number of facilities that report some value. This is a very, very highly requested indicator in DHS 2. And even though it's not related to data quality necessarily, I just want to make the point clear that using predictors, you can count the number of org units that did something. So I want to know every org unit that recorded more than five malaria cases, or how many org units recorded more than five malaria cases. Well, you can actually get that number using predictors from aggregate data. One, a couple of words of warning here. Predictors have to be scheduled jobs, just like we talked about scheduling jobs and validation rules. Predictors have to be scheduled jobs. Predictors do also require quite a lot of processing on your CPU, on your servers. So if you have a lot of that predictors running, quite often, you can really text your server, just like we talked about with validation rules. So you have to be very careful about how many predictors you have run, when they run, and how much data they actually generate. Because these could all have server implement, yeah, they could all affect your server, excuse me. If you are a server expert or a server administrator out there, please feel free to talk to us about exactly how you should be considering how many predictors to run, when to run them, how much data to store. Because if you just set these up without considering how your server is performing, you could really set yourself up for disaster. So how do we make a predictor? Well, predictors are actually the value that's generated through a predictor is actually stored as a data element in DHS2. And the reason that this is good or is useful is that that data element can then be used in indicators, it can be used in validation rules, it can be used in anywhere that you use a data element. So again, predictors are very different than standard indicators. Standard indicators calculate values on the fly. They do not store those values. Every time you turn on an indicator, that value is calculated. Predictors actually calculate the value and then store that value as a data element so that you can go back and use it in other places. So how do we do this? We first make a data element, then we make the predictor, and we assign that predictor to store that value that it generates in the data element. Then just like with indicators and data elements, we have to put the predictor in a predictor group. Then we schedule the predictor group to run just like we did with the validation rules. And then finally we can put that predictor into a validation rule to allow us to get those outlier detection going. So how do we make the outlier threshold? Well, the first step is that you have to make your data element. And so I'm going to quickly cover how to make data elements. This is not a DHIS2 configuration course, specifically, but you have to make the data element first. And this is the screen to make a data element.  You have to give your data element a name, of course. You also have to give it a short name. Typically the short name is the same as the long name. In this case, we're saying A and C1 outlier threshold hyphen your name. And again, you're hyphen your name in case you're doing this right now, you're following along, you're able to recognize your outlier threshold from anyone else who's making those right now. Your domain type will be set to aggregate, your value type set to number, and your aggregation type set to sum. Then we need to go in and make the predictor. So again, we go to maintenance app. We scroll all the way down to the bottom of the maintenance app. You'll see the predictors there. You'll click on the predictor and you can click that blue plus button again, and you'll go into making the predictor. The screen you see here is actually how is the screen you would build the predictor in. Again, first step, as always, give it a name. Second step is, of course, you can also give it a short name and a code and a description as well. But the second compulsory step is to define the output. So we just made a data element. We need to go in and find that data element we just made and assign that data element to this predictor. Just to repeat myself, the predictor will store the value that is generated in that data element. We also have to define a period type. So the frequency with the predictor 1, but how will that aggregated value in that data element be stored? We're going to say monthly here. And then the next step, which is absolutely required, but it does not have an asterisk next to it. And so please hear me. You have to select an organizational unit group level, or sorry, organizational unit level. You have to select an organizational level for predictors. So here, the typical rule of thumb is select the level at which the data is captured against the values that will be used to calculate your predictor. Select that same level. So in this case, A and C data is coming in at facility level. So I want my predictor, I want the value that is generated to also be stored at facility level. So I'm selecting facility here. So please, you have to select an organizational unit level. If you don't, the predictor will not work. The next step is to define your generator. In the generator, this is where you actually put in the calculation for the predictor. And in the generator, you first have to define a missing value strategy. This is the same as the validation rules. And it will just say, if the values that are missing, how do I handle the values that are missing in the calculation that you're providing? The default is skip any values if it's missing. And the question is, is this usually good? And typically with predictors, it's not useful. We actually want the calculation even if there are some values missing. And the reason is for that, because we still want to calculate this value. This value is referencing previously reported data. So even if in this case, we're actually going to be looking at 12 previous months of data. So if we leave it to skip if all values are missing, or skip if any values are missing, then if it's skip if any values are missing, then if there's one month of where there is no data, then we won't actually generate our predictor. And that's not what we want. We actually want them to generate the predicted value for the average of the last 12 months, even if there is one of those months that doesn't have a value. Okay, again, I think this is something that's easier to show you than to to talk about on a slide. So I am going to go into my maintenance app. I'm going to scroll all the way down to predictors. I'm going to go into my generator. All right. And remember, we're making a predictor that is going to produce an outlier threshold for A and C one. So again, what is how do we calculate an outlier threshold? Well, the outlier threshold is the average plus three standard deviations of the value. So how do we do that? Well, in predictors, we are allowed to type in various mathematical operators. If you're curious on what all of these operators are, I think I have a slide on it, but you can also just Google DHS to predictors. And there is a clear documentation on all the various ones. But the for the one that we're going to use right now is AVG. And then that's average. And then we're going to find A and C one. And I'm just going to say A and C one visits close my sorry, close my brackets. And you see my translator is already working. So I'm taking the average of A and C one plus I'm going to do another open bracket three times the standard deviation and standard deviation is type STDDV another open brackets. I'm going to then add A and C one visits again. And to close right. So now it's actually translating properly. So we are taking the average plus three standard deviations from the average. Remember yesterday we talked about standard deviations and the bell curve three standard deviations off the average means that it's going to pick up any value that is 98% different than the average. Okay, 98% different than the average over all of the sampled values. Again, I have to give it a name for the sake of time. I'm just going to copy and paste that in there. Submit. Okay, here it is again, I'm back into my PowerPoint. So the formula for standard deviations is average plus the plus the data element plus three standard deviations three times STDDV and then A and C one. You might be wondering if this is case sensitive. In older versions of DHIS two, it is case sensitive. In newer versions, it is not. So if you're using DHIS two point, I believe three one or older, and you're using predictors, you need to put these in all capital letters. If you're using 31 or newer, so 31, 32, 33 or 34, you can put these in lowercase letters like you see here. Yeah, so here are the other functions for predictors. You can see that there's quite a lot like average count max median min standard deviation sum. These can be used in different situations. The next step is that we have to define our counts. Sorry for the spelling mistake here on count, but we have to define our counts. Now again, in this particular situation, looking at producing an outlier threshold, we want to reference the last 12 months of data. So we are going to say 12 sequential sample counts here. A sequential sample count is just what was the last period and how many of those periods do you want to count? So we're going to say our last period was months. We've already defined that elsewhere in the predictor. We're going to say 12. We want to look at the last 12 months of data. Our annual sample count, which is saying how many previous years do you want to reference? We're going to leave that one to zero. And then we have a sequential skip count. Sequential skip count will allow you to say I want to skip some number of previous samples. In this case, we're not adding a sequence. We don't need a sequential skip count. So we're not going to even add it in. So what does this actually look like? Let's pretend that we are in March right now. Okay, let's pretend that we are in March. And if we say a, and the numbers that you see listed here, these are months of the year. So January through December and then one, two, three, four January, February, March, April. Okay. So let's say that we are in April and we say we have a sequential sample count of 12. What will that do? Well, that will take the previous 12 months. So that would take from March to April of last year. Annual skip count is, annual sample count is zero. So we're just looking at just those last 12 months and our skip count is zero. So we're not skipping any values in the last 12 months. This can become more complex, of course, right? So for seasonal data, you typically have to have some combination of annual sample count and sequential sample count to be able to factor in the epi curve of malaria, that bell curve that you have of seasonal malaria or any kind of seasonal disease. I won't go into it now for the sake of time, but there is clear documentation on our website and our user manual on how to build out predictors using combinations of sequential sample counts and annual sample counts to factor in more seasonal data. So that is how you make the predictor that generates the outlier threshold. How do we then put that into our validation rules? Again, we want to have a validation rule that checks the ANC1 value against the ANC outlier threshold and say, if that ANC1 value is higher than that outlier threshold, send me an alert, send me a notification. Let me know that this value is 99% different than the average. Well, it's the exact same process that we just went through in building validation rules. Here, you can see, building out the validation rule, we give it a name, we can give it a description, again an instruction, you can define the importance. Our period type again is monthly, our left side expression is ANC1 visits, our operator is less than, and our right side operator expression will be ANC1 threshold. Again, validation rules need to be defined based on what we know to be true. In this case, we can interpret that to be ANC1 visits should be less than ANC1 outlier threshold. And again, that threshold value is a data element that is coming from a predictor. So what happens when we run this validation rule? We can see that we received a lot of validation notifications. And just looking at this one example here, we can see that we have a value for facility 583 in October 2019 that was reported a ANC1 value of 126, but our outlier threshold is 117.9. So it's saying, hey, look, 126 is bigger than 117.9, it should be less than, here's an alert. Before I cut over to revisiting some of the scheduling, I do want to quickly show you how you use predictors to count org units. And in this case, I'm counting the number of org units that have a stock out of some commodity. This is not related to data quality, it's just highly requested thing to know. And so in predictors, we can also put an if statements in our generators. And that if statement here, if you look at the translator, where it says valid at the bottom of the of the screenshot, just directly above that, you have the translation. And this saying if the stock out of RDTs number of days is greater than zero, count a one, if not record a zero. So what is that actually going to do? That's going to say that if you have more than one, or you have one or more days of stock out of RDTs that's recorded in your monthly reporting form, then it's going to count a one value. And that one will be saved as a data element against that facility. And you can use that value to then aggregate up the hierarchy and say how many facilities did I have a stock out of RDTs last month? Or you can even say put that value onto a map and you can make a map showing specifically, these are the facilities that had a stock out last month. That's how predictors can be used to count health facilities. Again, it's a little bit more an advanced concept. If you have questions, please send those on Slack and we'll be happy to come back to them. For the sake of time here, we don't have time to go into more advanced functionalities with predictors. But there is a lot that you can do with them. Hopefully you appreciate that. All right. So one additional point that I need to make is that predictors also have to be scheduled in the scheduler app. So it's a different job than the maintenance job that we use to make validation, to schedule validation rules. So we have our ANC outlier threshold and we are going to make the job type predictor. Again, you select the frequency that you want. Again, just like we did the validation rules exact same, you can select a predefined frequency and you can put in your own frequency through a chron expression or you can say continuous execution. Again, I highly recommend that you do not use continuous execution unless you are in a disease surveillance scenario and you're only using one or maybe two validation rules. The job type will be predictor. This is again different. The job type for the validation rule was a monitoring job type. This is a predictor job type. But the parameters are the same. So we have to define our relative start and our relative end. Again, rule of thumb, relative start negative 60, maybe negative 30. You just want to cover a few previous months, right? Relative end to being just one, which is tomorrow. And then we have to give our predictors into our scheduler. So you just type out the predictors here. You'll be able to select them and then you add the job. Now, let's say that you have some predictor jobs, then you have your analytics tables and your validation rule alerts.  If you're not a DHIS2 techie, you're probably not going to appreciate a lot of this. But the point that we made is that you have to schedule these jobs to run concurrently. You cannot schedule these jobs to run at the same time and they need to run in a specific order for you to actually be able to generate your validation rule alerts. So the first thing is that you schedule the predictor's jobs to run first. And again, you want to have all of these jobs run when the server usage is low, when there's not a lot of people on the database. The predictor jobs, for example, you see the example here on the right side of the screen, could run at say 11 o'clock, 23 on a Sunday. Very few people are going to be looking at DHIS2 at 11 o'clock on a Sunday. Then you have your analytics tables run after that. Again, the analytics tables are just a function that has to be performed in order to see the data on the dashboards or in the data visualizer on maps, etc. So you want those to probably run right after their predictors. You can have that run maybe an hour later, run that at midnight on Sunday. Analytics tables, depending on the size of your database, may take a while. So if you give yourself a few extra hours of buffer and say, then you want your validation rule alerts jobs to run at maybe zero three. So a few hours after your analytics tables. And if you run them in this order, that means that your predictors come first. Those predictors are then able to be seen on your dashboards if you want, if you have them there. And then they'll be able to be pushed out in your emails. If everything goes properly, then this will all happen when you're asleep. When you wake up in the morning, you'll see an email from DHIS2 saying, hey, look, these are the alerts that were generated last night. Okay. There is some question already posted in the Community Practicer on the Slack channel around how do I get email or how do I configure DHIS2 to send an email? Well, the reality is that you have to generate an email service from your service provider. DHIS2 does not have a built-in email host. This has to be provided from your service provider. So if you are a Ministry of Health, and you are using a telecommunications company in your country, hosting your DHIS2 instance, then or hosting, say your email service for your ministry, that host, that company, whoever it is, needs to provide an email host or an email endpoint for your DHIS2 instance to be able to send emails. Again, not something that University of Oslo can provide you. This has to come from whoever is hosting your email service. Many of you are probably using Google as your default email service. So if you have like a Gmail, for example, and if you are using Google, then we've given you some of the guidance on how to configure this. But you have to provide a host name, a port number, a username, a password, a username, a password. This is for your email service. This is not for your DHIS2. You need to provide a TLS, an email sender address, and an address to send test emails. Again, all of this has to be provided by your email service provider. We cannot provide this to you. This has to come from whoever is hosting your email service. Any telecommunications company that hosts email services should be able to provide this to you. These are fairly basic things to be honest with you. The example that you see here is if you have your email hosted by, say, Amazon web services on the left side of the screen. Like we do here at DHIS2, we have our email hosted by Amazon web services. So that would be our host criteria. Of course, you don't have our password, so you can't use the same thing. Okay, so we have maybe just 10 more minutes for any burning questions. Nora, is there any terrible issues out there, or what's the most terrible issue out there? Yes, Scott, there were a few questions. I'm just going through them. Do you want to introduce yourself from derivative? Does predictors work in event and tracker 2? How does that differ from program indicators? That's a really good question. Yes, you can use an event and tracker data in predictors. The difference between a program indicator is that that predictor value is actually saved as a data element. So you're able to then use that predicted value in other calculations, in validation rule notifications, anywhere that you can use a data element. And that's very unique in that you cannot do that with a program indicator. There's also different types of calculations that can be done in predictors that cannot be done in program indicators. Predictors can also incorporate values across multiple programs. So that could be very useful to you that if you have like a program for A and C, a program for immunization, a program for birth or follow-up or something like that, and you want to have a value across all of those different programs, you can use that to make a single calculation. You can do that in a predictor. You cannot do that in a program indicator. Any other questions? Yes, there was something about can you use data elements across different data sets? Yes, of course you can use any combination of data elements that you want to make a predictor. And then for the general QA, that the number of from Fernando, the number of standard deviation to add to the average to set the threshold to vary depending on the value we're tracking, but a good rule of thumb is three. And I think that is what you are more releasing. Yeah, I think he said it perfectly. I would totally agree. I think three is a good rule of thumb. We don't have the intelligence in DHIS to yet to be a little bit more flexible there. We would like it to help the user define what would be an appropriate number of standard deviations. We are kind of starting to explore how to do that, but right now I think you're absolutely right. Just set it to three. Three is probably not going to steer you wrong in most cases. Then there's a question just above that from Pearl from Cameroon. Can you explain the significance of each term? Zero comma one, zero, zero comma one comma zero. I think that's a chron expression. That could be a chron expression. It could also be that he was referring to the if statement. So I could go in a little bit more detail on the chron expression. Let me just get back. Let me go to the scheduler app. Okay, so it looks like some folks have already done this. That's great. So the chron expression, if I just make a new job, I've got to define my job type. Again, the monitoring job is for validation rules. The predictor is for predictors. So I'm just going to make a validation rules. My chron expression, I have the ones that I can already choose. So like every day at midnight. And like say every week and this would be every week at 3am. So I'm just going to say test, add job. Yeah, okay. So that would be the first day of the week at 3am. So let me kind of explain this to you a little bit more clearly. So each one of these values, so we have zero, zero, three, question mark, asterisk, and then m-o-n. Well, hopefully you understand the m-o-n. That's Monday. So each one of these actually represents a unit of time. So we have second minute, so zero and zero seconds at zero minutes on the third hour. And then we have day and month. So the day is defined as Monday. And the month is, or sorry, we have a day and week and then the day of the week month. So we have this running every Monday. Now, I know that is kind of confusing to folks. Please just Google it. So if I just Google chronic expressions, there are free formatters online for building chronic expressions. So for example, if I want to say I want something to run every month, then, sorry, I want something to run every day starting on Sunday, then it automatically generates a chronic expression for me. If I could say I want every day on the first day of the month, then you see it generates a chronic expression. So if I copy this, go back to DHS too. Scott, there was an update about that question from the user. Apparently it's about predictor configuration. Okay. Well, let me just finish this then. So I've just copied and pasted the chronic expression for every day, the first day of every month here.  You can see my next execution is November 1st at midnight. Okay. So you see that there. So that's how you can do chronic expressions. The actual question was on setting the org unit level for the predictors. Is that correct? It was to come facilities with dropout drugs. Yeah. So this is not, you know, actually in two weeks, we have an entire academy on supply chain and building predictors for the supply chain. So I recommend that you attend that academy if you really want to specifically know how to do that. But very quickly here, let me just show you. If I want to count the number of facilities that have any specific value that's recorded, I go into my generator and I type if open brackets. And I'm just going to say acute flaccid paralysis death under five just for the exam. And I want to say if acute flaccid paralysis deaths are greater than say five, then record one. If else record a zero. Now what does this predictor do? You can see that it is considered valid. This will say if that health facility that month recorded more than five acute flaccid paralysis deaths, then it will count one. So the way you translate these if statements say if this then this if else then this. So if this is greater than five count one if else count zero. All right. So this is like this is basic basic basic basic computer programming basic if statements. But here that's what it's going on. So if if this is greater than five, then count one if else count zero. And so what will this do? This will say, oh, this facility had more than five record a one value. And that one value again is saved as a data element. And that data element can be aggregated up. So you can say, you know, how many across the entire country, how many health facilities that I have more than five acute flaccid paralysis deaths this month, and you'll have a number there because for every single one that does it's counting a one. Okay. Now this is a very basic example. You can make these much, much more complex. And you'll actually if you do come to the supply chain academy in two weeks, you'll see that we've made some that are much more complex than this. But this is a very basic one to be able to count the number of facilities that record any particular value.