Good day, everyone. This is your lecturer, Monica Wahee. And we're going to start now with section 1.1. What is statistics? So here's our learning objectives for this lecture. At the end of this lecture, the student should be able to state at least one definition of statistics. Yes, there's more than one. Give one example of a population parameter and one example of a sample statistic. Also, the student should be able to classify a variable into quantitative or qualitative and as nominal, ordinal interval or ratio. So what we're going to cover in this lecture is first I'm going to go over some definitions of statistics. Like I said, there's more than one, but they all sort of relate to the basic concept of why you're doing statistics and especially not math. So what's the difference, right? Then we're going to go over population parameter and sample statistic and you'll know what those mean at the end of the lecture. And finally, we're going to go over classifying levels of measurement. So let's start with the definition of statistics. And so we're going to go over these concepts like what it is. And also I'm going to define for you the concept of individuals versus variables. You may know definitions for those words already, but I'm going to give you them in statistics ease. And then I'm going to give you examples of statistics individuals and variables in healthcare. So here are the definitions. What is statistics? Statistics is the study how to collect, organize, analyze and interpret numerical information and data. Well, that sounds pretty esoteric, right?   Well, do you go?  So how, how do you do that? You kind of have to analyze it. You kind of have to interpret it. So it's not that easy. Um, so statistics is both the science of uncertainty and the technology of extracting information from data.  You don't know for sure. But, uh, so it's a science of uncertainty. If you look on Yelp, and you're seeing almost everybody's giving it a four or five star, maybe it's going to be good for you, right? But you don't know, maybe there's new management. That's the uncertainty. So statistics is used to help us make decisions, not just whether to go to the restaurant or not, but important statistics such as in healthcare and public health. Well, I guess if it's an expensive restaurant, maybe it's important. But anyway, in healthcare and public health, you really need these statistics because they really guide you. Like for example, let's think of the Center for Disease Control and Prevention in the United States. So what do they do? They spend the whole year studying the different flu viruses that go around because there's more than one. They spend the whole year doing that. They organize, analyze and interpret, uh, numerical information and data about these different fact, uh, viruses, the different influenza viruses that are going around. They extract that information. And you know what decisions they make? They make the decisions about what viruses to include in the next year's vaccine. Are they always right? Sure enough, they're not.  Well, you know, give them a break. It's the science of uncertainty. They, it just didn't work out that time. However, this is probably better than just randomly guessing, right? So that's statistics for you.  Now, if you're outside statistics, you know that individuals are people, right?  But when you enter the land of statistics, there are specific meanings to these two words. Individuals are people or objects included in a study. So if you're going to do an animal study with some mice in it, those would be the individuals. If you do a randomized clinical trial, and you include people who have Alzheimer's in it, then patients are your individuals. But we do a lot of different things in healthcare. We sometimes study hospitals like the rate of nosocomial infections, in which case, if you're looking a whole bunch of different hospitals, those would be the individuals. Sometimes we look at states, rates of infant mortality, for example, in different states. In that case, states would be individuals. So as you can see at the bottom of the slide, a variable then is a characteristic of the individual to be measured or observed. I give some examples on the slide. But like I was saying, you know, if you wanted to study a hospital, for example, I gave you the example of a variable of a rate of nosocomial infections. You could also have other variables about that individual or hospital, like the rate of in hospital mortality. And so as you can see, one of the things we do in statistics is we sit down and we decide, well, who are going to be our individuals that we're going to measure? And what variables are we going to measure? So I just threw up here a few examples of different kinds of individuals we have that we use a lot in healthcare and public health. And an example of just one variable about those example individuals, but there would theoretically be many variables about them. And I just want you to notice a lot of times the individuals are geographic locations. Other times they might be institutions, like I said, like hospitals or clinics or programs. There's other things that they are, but these are just kind of the big ones. So as I was describing, and just to review what I went over, statistics is used in healthcare and other disciplines to aid in decision making. Like I gave the example of the CDC and their vaccine for influenza. And so therefore it's really important to understand statistics because you need to understand these processes in healthcare, like how do we figure out what to do? Like not only what do we do, but how do we figure out what to do? And that's really important because we use statistics a lot in healthcare. Now we're going to move on to talk about what a population parameter is and what a sample statistic is. So we're going to go over first the definition of a population and the definition of a sample. So you're sure about what those mean. And we're going to talk about the data about a population and the data about a sample and how those are different. And then we're going to get into what I was just describing parameters and statistics and I'll give you a few examples. So let's start with what is a population? Again, another case where you just have a normal old word, but it has a special meaning in statistics. Well, it's a group of people or objects with a common theme. And when every member of that group is considered its population, right? So here's just one example. So the theme would be like nurses who work at Massachusetts General Hospital. So the population then, if that was your theme, will be the list from human resources of every nurse currently employed at MGH. Now it really does depend on how you define that theme. Like I could have said, nurses who belong to the American Nursing Association, right? And then we'd be looking at a different list. I could say nurses who live in New Orleans in the city limits of New Orleans who live there, right? Then we'd be looking at a different population. So it really has to do with the details of how you describe the theme around that population. But the point is, once you describe that theme, the population is every single individual in there. So then what is a sample? Well, it's a small portion of that population. It can be a representative sample, but it can also be a biased sample and we're going to get into that. So let's just go back to MGH and think, let's say we were going to survey a sample of the population of nurses at MGH. Let's say we only surveyed nurses in the intensive care unit. That would be a sample, but not a representative sample. So it would be a small portion of that population, but not a representative one. Probably more representative would be if we asked at least one nurse from each department. And so I just want to get in your head that the whole concept of sample is, is that it's just a small portion of the population. And it's not a portion of some other population. It's just that one. But the problem is you can get a biased one or a representative one. So you have to think about. So when you think about it, if you've got a whole population, then you would get variables about each individual in that population. And those variables would be your data. But if you chose samples, then you know, just a portion will be a lot less work, right? You'd still have to get variables about those individuals, but there's way fewer individuals. So it would probably be easier. So in population data, data from every single individual in the population is available. And that's called a census. So I knew a person who decided to do a survey of every single professor at a college. She didn't take just some professors from each department. She sent the survey to every single professor. So she did not use a sample. She used a census. But in sample data, the data are only available from some of the individuals in the population. So if we go back to the researcher I described, if she had only taken some of the list, the email list of the professors at that college, then she would have been surveying a sample. And that's actually very commonly used in research studies, especially of patients. Why would you need to go get every, for example, kidney dialysis patient and study every single one? You only need a sample. And why is that? Because we have statistics. So I'm going to just give you a few examples of real population data in healthcare. You're probably familiar with Medicare. Medicare is the public insurance program in the United States for elders. So even my grandma was on Medicare when she was alive and she was not a U.S. citizen. She was from India. So we really do a good job of covering our elders in the U.S. with Medicare. In fact, I even read a statistics that said almost 100% of people age 65 and over are in Medicare. And so therefore, if you download data from Medicare, they make it confidential, you know, they just replace all the personal identifiers. But there's this thing called the Medicare claims data set for every single transaction that happens. Like if you're in Medicare and you go get some treatment, that's in there. So it has all the insurance claims filed by the Medicare population. Because it has everybody, everything, then that is population data.   And the idea is to try to get every single person in the United States to fill out that survey. And that's called the United States Census. So now I'm going to give you sort of a mirror image of the sample data. Okay. Remember how I was just talking to you about Medicare. People who are enrolled in Medicare are called Medicare beneficiaries. And Medicare care is what they think. So they do a survey of a sample of individuals on Medicare. And they do this kind of often. I think they do it once a year. Sure. And it's a phone survey. They only do a sample because they're going to use statistics to try and extrapolate that knowledge back to the population of Medicare beneficiaries. Also, in case you noticed, the United States Census only takes place every 10 years. Do you think changes happen in between? Yep. Lots of changes. Like even just think about Hurricane Katrina. That's very sad. It changed the population distribution in Louisiana very, very dramatically. And also other states around there. So how did they keep up? Well, they used the American Community Survey. The government does this, the United States Census Bureau. And that, again, is done by phone. And that's conducted yearly. And it's a sample. And so the US doesn't know exactly how many people would be in Louisiana or anywhere else. But they can use statistics to extrapolate that from the sample of the American Community Survey. I want to just do a shout out to statistical notation. So from now on, when we see a capital N, like let's say you saw capital N equals 25, then you can assume that 25 means a population. That's just kind of a secret code we use in statistics. However, if you saw a lowercase N, N equals 25, and it was lowercase, then you could assume that this was a sample of the population. And again, it's just kind of like a secret code. You have to pay attention. When I'm talking and I say N and you can't see uppercase or lowercase, you don't know if I'm talking about a population or a sample. Now I'm going to get into the concept of parameter versus statistic. I want you to notice that the word parameter starts with P, PAH. So a parameter is a measure that describes the entire population. So for instance, anything that would come out of that whole Medicare claims data set or that whole United States census would be a parameter. On the other hand, a statistic, statistic starts with S, and statistic is a measure that describes only a sample of a population. Here we have again a situation where the word statistic is used like daily on the news. In fact, sometimes I hear on the news something like, oh, look at the rate of HIV in Africa. It's going up. That's a terrible statistic. I agree. It's terrible, but they mean parameter because they're talking about all of Africa, every single person in Africa. If the rate of HIV is going up in Africa, they mean a parameter. They don't mean a statistic. So here's an example of parameters and statistics that are based on the same population. So for example, the mean age of every American on Medicare is a parameter. That's every single person. However, remember the Medicare beneficiary survey? That's just a sample. So if we took the mean age of those people, we would just have a statistic. And again, you just have to pay attention because if you listen to the news, you'll hear them use the word statistic to mean both parameter and statistic. But in this situation with when you're practicing in the field of statistics, it's very important to point out when the number you're talking about comes from population versus comes from a sample. So you should really use the term. This is a parameter if it's from a population, or this is a statistic if it's from a sample. And so again, don't get confused. If you're listening to someone talk in a lecture or in a video, you might want to look for clues that a number is a population parameter or as a sample statistic. If you hear that the data set that they use encompasses an entire population and usually that's the kind of stuff done by governments. Like remember when I was talking about the rate of HIV in Africa, that probably be done by governments or the United Nations or the World Health Organization. So when you're talking about numbers that might have come out of an entire population, usually done by the government, that's probably a population parameter. Clues that someone's talking about a sample statistic is if you hear them talking about a study that recruited volunteers. Well, then if it's volunteers, they didn't get everybody in the population. So it's going to be a sample. Also like surveys, for instance, surveys about who people are going to vote for, you know, public opinion surveys, they're never going to ask some every single person in a state who are you going to vote for? They'll just ask a sample. So if you hear about a survey, you might even have them tell you say n equals maybe a few thousand people because that's all they surveyed. And so that's a clue that we're talking about a sample statistic rather than a population parameter. Now I'm going to talk about the difference between descriptive statistics and inferential statistics. But first I'm going to remind you what the word infer means. So infer means to kind of get a hint from something indirectly. It's kind of the compliment to imply. So if I said my friend implied that I should not call after 9pm and I figured that out, I would say I inferred that I should not call my friend after 9pm. Okay, so in inferential is what I'm going to talk about next, but first I'm going to talk about descriptive. Descriptive is pretty easy because you can do it to samples and you can do it to populations, well, variables from samples and populations, right? And so descriptive statistics involve methods of organizing, picturing and summarizing information from samples and populations. It's basically just making pictures of it, right, like look at that bar chart. And that's just a simple picture and that can be made with just about any data. You get data from serving people at work. You get data from surveying your friends, what they're going to bring to the potluck. Any of that can be used. You can go download the census data. You can make descriptive statistics out of that. But there's something very special about inferential statistics. And that involves methods of using information from a sample to draw conclusions regarding the population. Therefore, inferential statistics can only be done on a sample. And therefore, and that's why that's called inferential, right, because infer because the sample is going to give a hint about what the population is, right? It's not going to say it directly, which is annoying, right? But that's that uncertainty thing I was telling you about. So the sample is going to imply something, well, we're going to infer something from the sample about the population, right? So that's what inferential statistics is, is where you take a sample and you infer something about the population. Whereas descriptive statistics is more loosey goosey, you can just do that to samples and populations kind of like make pictures out of it, right? So in statistics, it's really important to properly identify measures as either population parameters or sample statistics, because as you can see, you can only do inferential statistics on samples. And so you have to really know what you're doing when you're doing statistics, what you're talking about, because different types of data are used for parameters versus statistics. Alrighty, now we're going to get into classifying variables into different levels of measurement. So remember our variables, right? Like we have individuals, and then we have variables about them. And those variables actually can only fall into two groups, quantitative versus qualitative. And then depending on which group they fall into, you can further classify them as interval versus ratio, or nominal versus ordinal. And I'm going to give you some examples of how to classify a few health care data types of variables. Alrighty, so I like to draw this picture. It's a four level data classification. I'll draw it solely here for you. So we start with human research data. That's what I like to start with. Alright, so we're going to split that into two. Remember I said that we're going to start by talking about quantitative. Another word that's often used for that is continuous, but we're going to use the word quantitative. So what does that mean? That is a numerical measurement of something. So like this gives an example of temperature. So something with a number in it. I always think if I can make a mean out of it, it must be a quantitative variable, right? And so here's an example of quantitative variables. So time of admin, right? So imagine that you work a shift in the ER, right? And from maybe 8pm to 12, like midnight, right? So you have this four hours, and you could say what the average time of admin would be for those who got admitted to the hospital. You know, somebody got admitted at like 8 o'clock and then somebody at 815 and whatever, you could put that together and you'd say what the average time was. Also, like if you were doing a study and you as you were saying patients with a particular condition like Alzheimer's disease, you could ask them their year of diagnosis and then you could make an average of that. And so you know that that is quantitative. Cystallic blood pressure is also numerical and platelet count. And these are variables we run into all the time in healthcare. So we're used to that. This is quantitative. Now we'll get back to our picture. So that's one side. So what if it's not quantitative? What else could it be? Well, the only other category it could be is categorical or qualitative. I use a term qualitative, but some people use a term categorical, but that's kind of what it is, is that it's a quality of something or a characteristic of something like sex or race. So here are some qualitative variables in healthcare, like you can have type of health insurance, like whether you're on Medicare or Medicaid or different types of private insurance. Those are all just categorical, right? You can't make a mean out of that. Also country of origin. If you're in a group of students and there are international students in there. Well, what countries are they from, right? Well, you can't make a mean out of that. Also, you have situations where you do have numbers involved like the stage of cancer, right? That's depressing stage one cancer, stage two cancer, stage three. Well, you never can make a mean out of the stage of cancer, you wouldn't say, well, the mean stages is 1.4 or something like that. It's just a category. And of course, stage four is a lot worse than stage one. You know, they're not just equal categories, but their categories. Same with trauma center level level for trauma center, where you wouldn't make a mean out of the number of after the term trauma center, right, like what level it is. But you could say, well, in the state, maybe so many percent of our trauma centers are level for trauma center. So it's really just a categorical variable, even though there's a number involved. All right, so let's get back to our diagram. We figured out how to take any variable and first split it into one or of two categories, either either quantitative, if it's numerical, or qualitative, if it's a characteristic. Now we're going to just concentrate on quantitative because we're going to separate those variables into two categories. And the first one we're going to look at is interval. And the second one we're going to look at is ratio. So if a if you happen to decide a variable is quantitative, then it could be interval or ratio, but not if it's qualitative. Okay, if it's qualitative, it doesn't get to do that. So let's look at interval versus ratio. So on the left side of the side, we have interval, which is where it's quantitative and the differences between data values are meaningful. And ratio has the same thing, the differences between the data values are meaningful. What does that mean by that? Well, remember how I was talking before how level one trauma center and level two trauma center that that those are really categories and not quantitative variables, because the difference actually between them is not equal. And especially if you think of job classifications that might go in 1234, like nurse one, nurse two, nurse three, nurse four, or I worked at a job where we had office specialist one office specialist to office specialist three. And you know what? The deal for going from office specialist two to office specialist three was really hard. You really had to do a lot there. But to go from one to two wasn't that hard. So that was a categorical variable, right? Because the differences between the values were meaningless. Okay, like the difference between OS one and OS two versus OS two and OS three, they weren't equal. Whereas when you're dealing with a quantitative variable, regardless of whether it's interval or ratio, you're talking like years or systolic blood pressure. One year for you is one year for me. So that's fine, right? But here's where the difference comes in between interval and ratio. So all quantitative variables have meaningful differences between their data values. But this hair splitting thing here is that in interval, there is no true zero. And in ratio, there is a true zero. And this is how I try to think about it. An interval means kind of like a space between two things. Like if you think of the word intermission is kind of like an interval, it's like an interval of time during a show where you get to get up and go to the bathroom and get some coffee. So that's interval. And so if you have something that's a space in between, that's not going to have a zero, it doesn't really start anywhere or end anywhere, it's in between. Whereas ratio, how I remember that is, I don't know if you remember from like high school, but you can't have a zero on the bottom of a ratio or a fraction. So that's the way I use a mnemonic that ratio means that you cannot have a true zero. But how does this work out literally, we'll show you. So let's go back to those examples, I showed you of quantitative variables, right, because those are the only ones we have to make this decision. about whether they are interval or ratio. So these are these examples. Now, I'm going to remind you that ratio has a true zero. Remember that little mnemonic I said, like, don't divide by zero. And so, you know, like an ratio, so they have a true zero. Well, let's think about it. It's not very pleasant to have a zero systolic blood pressure, because you'd be dead. Same with the platelet count. But it is possible, right?  So as you probably just guessed, ratio is where it's at in health care. There's not a whole lot of times when we have interval data. But we do, you know, anytime you have a time, so you've got to keep that in mind that if you want to split your quantitative variables into either interval or ratio, you got to keep this in mind the difference between the true zero and the no true zero. Okay, here's our handy dandy diagram. We've just gone through the tree, classifying quantitative data into interval versus ratio. Now, let's go pay attention to the other side of the tree qualitative. So how do we split those? Well, we can split those into nominal versus ordinal. All right. So nominal applies to categories, labels or names that cannot be ordered from smallest to largest. Okay, like I kind of think of when they have an advertisement, they say for a nominal fee, you can do this. It means it's small, like there's almost no difference. And so that's why I say, there's no difference, it's not smallest to largest, it means they must be equal. That's how I remember it in my mind. But then ordinal applies to data that can be arranged in order and categories. But remember that thing I was saying about quantitative, it's not quantitative, right? Because the difference between the data values, either cannot be determined or is meaningless, like I was talking about with cancer, especially, you know, if you go from stage three to stage four, that's materially different than stage one to stage two. So you really can't determine those things. So this is where we're going to get into that it's ordinal, it's arranged in categories that can be ordered from smallest to largest. So remember our old friends that I threw up there before of these examples of qualitative variables in healthcare. Well, let's just reflect on this nominal cannot be ordered, right? So that would be more like type of health insurance and country of origin, because they could all be equal. Whereas ordinal is going to have a natural order, even though the differences between the levels is meaningless, which is what makes it so different from a quantitative variable. So which is why it stays on the qualitative side of the tree, it just gets labeled ordinal. So what you want to do is if you think you have a qualitative variable on your hands, look for a natural order. If there is one, it's ordinal. And if not, it's nominal. So all data can be classified as quantitative or qualitative. So if you have a variable, that's the first split you can make is the difference between quantitative and qualitative. But once you do that, you can further classify it as interval, ratio, nominal or ordinal. And it's really important to know how to classify data in healthcare as you'll find out later, because depending on how you classify it, you might be able to do different things with it in statistics. Alrighty, so what we went over was the definition of statistics. And we talked a little bit about why you use it and how you use it, especially in healthcare. We went over what it means to talk about a population parameter in the sample statistic. And we went over some examples about them. And then we talked about classifying variables into the different levels of measurement, and even talked about a few examples there. So I hope you enjoyed my lecture.


I want to talk to you about the greatest prayer warrior on earth, and he prays for you daily.  Romans chapter 8, I'm going to read verse 26 and 27, and the Holy Spirit helps us in our weakness. For example, we don't know what God wants us to pray for, but the Holy Spirit prays for us with groanings that cannot be expressed in words, and the Father who knows all hearts knows what the Spirit is saying for, the Spirit pleads for us believers in harmony with God's own will. The Holy Spirit is the greatest prayer warrior of all time, and the Holy Spirit prays for you. Now notice the scripture says here, and the Holy Spirit helps us in our weakness. The grace of God is the glue that holds together all of the broken pieces of our lives. God's power sustains us, and as we surrender those weaknesses to the Holy Spirit, those weaknesses in surrender become strength. When we rely upon the person of the Holy Spirit, our walk with Christ is simple. When we try to do it through religion or man-made efforts and protocols, we begin to become spiritually exhausted, weighed down, confused, even sometimes cynical because things aren't working exactly the way we want them to work, but when you rely upon the strength of the Holy Spirit, you're like an eagle soaring on the winds.  In our weakness, we don't know what to pray. In our weakness, we lack desire for the Word of God. In our weakness, we tend toward disorder. We're pooled toward sin. The pool of the world becomes strong without the power of the Holy Spirit. In our weakness, we don't know how to worship. In our weakness, we don't have the boldness for evangelism. In our weakness, we habitually sin. In our weakness, we lack peace, we lack faith, we lack clarity, we lack joy, but the Holy Spirit, thank God, helps us in our weakness. What does that mean? It means that he supplements those broken areas of our lives with his strength. He gives us that fire. He gives us that passion. He gives us that spiritual life and vitality that causes us to become people of prayer, people of the Word. Think about the fact that sometimes you go about your day possibly neglecting the things of God, and then suddenly this strong desire seemingly out of nowhere is produced within you to pray, to read the Word. Maybe a strong conviction comes over you about the things that you're doing or the things that you're thinking or saying, and that pool comes from the Holy Spirit. He faithfully helps us in our weakness and many times we do find ourselves in weak places. We have the tendency to wander. We have the tendency to become weak in the Spirit. We have the tendency to neglect spiritual duties and practices and responsibilities, and that's when the Holy Spirit begins to help us. The Holy Spirit helps us in our weakness. Thank God he does it. Then the Bible says, for example, we don't know what God wants us to pray for. So how many times have you gone before the Lord, committed to pray, and you say within yourself, I'm going to pray for an hour, or you say I'm going to pray for my city or for my loved ones. I'm going to pray for the ministry. I'm going to really seek the face of God. You pray for what seems like 30 minutes.  What do I say when I pray? Am I supposed to walk around? Am I supposed to sit? Is it okay if I lie down? Am I supposed to speak it out loud? Can I say it just within my thoughts? How do I pray? What do I pray? What am I supposed to say? Maybe you've heard those stories from people who talk about how they spend hours with the Lord, and you say within yourself, I want that, but I don't know what to pray. I wouldn't know what to say for three hours. Maybe you're saying that within yourself. Well, this is where the Holy Spirit comes in. For example, we don't know what God wants us to pray for. Now watch this. This is powerful. But the Holy Spirit prays for us with groanings that cannot be expressed in words.  Think about how a grandparent prays for a grandchild.  Think about the passion and the love and the fervor and the strength and the might behind those prayers, the sincerity behind those prayers, the love behind those prayers.   He loves you with an immensely strong love. The scripture declares, I've loved you with an everlasting love. No love like it. You've heard that the father loves you. You've heard that Jesus loves you. But consider the fact also that the Holy Spirit loves you. The Holy Spirit loves you. And he prays for you. Now the scripture here tells us that he helps us in our weakness, meaning he's aware of our weaknesses. He's not surprised by our weaknesses. He's not surprised by our mistakes. He's not surprised when we wander astray like sheep. But the Holy Spirit patiently, faithfully guides you back to the things of God, brings you back to him. And the scripture says very clearly here that he prays for you with groanings. What does that mean, groanings? This is to pray with might, with force, with intense desire that cannot be expressed in words. I dare say that if you could see visibly, physically, the Holy Spirit praying for you, you would see him face down on the floor, tears streaming down his face. I would even go far as saying, as his fist would be pounding on the floor as he prays for you, his voice would shake the room because he prays with you. He prays for you with groanings that cannot be expressed in words. And he prays for us despite our weakness.   What a powerful truth to know that we have such a friend. When you feel like giving up, when you feel like you don't know what to pray, when you wonder if anybody cares, when you wonder if anybody prays for you or thinks about you, the Holy Spirit does, and he prays for you with such might, such power. He prays for you with such love. And here's what happens. And the Father who knows all hearts knows what the Spirit is saying. For the Spirit pleads for us believers in harmony with God's own will. As you look throughout the Scripture in the Old and the New Testament, you're going to see a common truth threaded throughout all of the Scripture. You're going to see that God embraces the humble. What does it mean to be humble? People who are humble acknowledge their need of God. They acknowledge that they're helpless without him. And they constantly plead with God, saying things like, God, don't let me wander. God, give me a love for your word. God, give me a desire to fulfill your will. It's to pray according to God's will. The Holy Spirit pleads for us believers in harmony with God's own will. What does this mean? It means that the Holy Spirit pulls us toward the purpose of God. It means that the Holy Spirit inclines our hearts to his word. In those times of life where we feel like we're drifting, in those times of life where we feel like we don't have the spiritual strength to continue, where we feel like we're failing in all of our responsibilities, the Holy Spirit comes alongside of us, prays for us like no one else can pray for us, and he pulls us back on track. He takes us back to the place of harmony with God's will. While we have the tendency to wander, the Holy Spirit keeps up with us by doing spiritual maintenance. You see, so many times we look at our spirituality and we imagine that we have a list to fulfill. If you're like me, you're overwhelmed sometimes when you read the scripture and you realize that there are countless ways that you're not like Jesus. I don't know how many times I've read the word and just said, Lord, there's so many ways I'm not like you. Help me to become more like you. I want to be more like Jesus in every single way. And if you're not careful, you begin to become overwhelmed because you create this list and you say, okay, I need to change my character there. Maybe I can manage my anger there. Maybe I can become more patient here. I got to deal with that sin over there. I got to change my mindset over here and I have to change the way I interact with these people over there and then add to that. I have to pray this often, read this much of the scripture. I have to go to church. I have to attend those meetings. I have to be a part of volunteering in my community. And all of these things begin to stack up and we feel overwhelmed because we imagine that we have this long list to fulfill. And yes, we have those responsibilities. Let me make that very clear. We have those responsibilities as believers, but here's the wonderful truth. God is not looking for you to go down that whole list. He's looking for you to do one thing and in doing this one thing, you will fulfill that list. Don't be overwhelmed. Take that list of all those things that trouble you about yourself and give them to God and then do one thing, surrender to the Holy Spirit. And what does he do? He pleads for us believers in harmony with God's own will. I tell them all the time, Holy Spirit, I'm your responsibility because I'm surrendered to you. Holy Spirit, I'm your project because I'm surrendered to you. Don't let me go astray. Don't let me lose that love for your word. Give me a passion to do your will. Give me a desire to live like you want me to live. That is produced by the Holy Ghost who prays for you with groanings that cannot be expressed in words. Father, I pray in the name of Jesus for that one receiving this prayer now. And Lord, I ask that you would begin to strengthen them by the Holy Ghost. Thank you, precious Holy Spirit. I want you to say that out loud, even write it in the comments. Just say thank you, Holy Spirit. Holy Spirit, we thank you. We honor you. We love you. Thank you for helping us. Help us now to surrender to your work in our lives. In the mighty name of Jesus, we pray, I want you to say it because you believe it. Say amen. Well, if you were blessed by that message, don't forget to leave a like on the video and subscribe to EncounterTV. Click that notification bell when you do. Also, you can help our ministry continue to do its work all around the world by becoming a monthly ministry supporter for $10, $30, or $100 a month. Just go to davidhernandezministries.com slash partner for information on becoming a partner with our ministry.  Until next time, remember, nothing is impossible with God.


Secular powers are ruling the globe right now. These kinds of policies and plans that they openly speak about and roll out, this is on the basis of secularism. And maybe you're not very well read, but if you look at some of these atheistic philosophers like Yuval Harari or Klaus Schwab, you can see exactly the kind of plans that they have for the human race. Unfortunately, people like Richard Dawkins aren't really clued into a lot of these realities, so maybe you need to find better atheist friends. Yeah, you hear that, Matt? Richard Dawkins is not elite enough for the atheists. No, I said he's not smart enough, that's why I said.


Everybody forced here ripping 2022 immaculate football hobby four box or six box full case number four pick your team style Alvin S. Dolphins and Saints Andrew a Vikings Andrew C Bears Anthony S. Broncos Armando with the Chargers Brian S. Falcons Karla with the Jets Chad R. Seahawks Charles K. Washington David S. Texans Edward P. Cowboys Ravens George K. Bengals Henrik J. Bucks Hilton with the Packers Jackie Y. Rams Jonathan B. Bills Jordan H. Chiefs Jorge R with the Jaguars Justin P with the Giants Kamoran with the Raiders Kyle M. Panthers Matt M. Lyons Mathias with the Browns Michael B. Colts Orin W. Steelers Robert R. Cardinals Sean M. Niners and Titans Steven H. Eagles and Zach B with the Patriots Good luck y'all. Yep, Sam will break in and about Couple hours here 5 p.m. Start time the night time breaks guys again all baseball sold after looking for baseball Check the baseball channel tomorrow and the main channel tomorrow Get your spots For real this time Jake's calling a shield. He's a ha ha got everybody's hopes up last time He's calling it for real though. There is that you know who that is I don't buy ends up one nothing on the aggregate right now.  I don't know if that's how it goes. Yeah 799 clearly immaculate Jersey Carson strong Eagles is black and yellow killer. She's not ready yellow killer fellow Black happy jack ready yellow. Okay Jim auto 10 of 49 Raiders on the Jersey card Jim auto. What is that dude? What is going on here? Is that a glove four of five John Metsch of the third? Gloves Texans Nice one Houston, right? Yeah. Yeah Drawing agri-force extra time that could lead to PK's but yeah Would be extra time Got a eye black auto 43 of 49 Fran Tarkin center for the Vikings nice Fran Good vet hit for the Vikings and true RPA jets breeze haul 43 of 99 three colors Awesome hit for the Jets Hang out of the shop those games over I won't have this at home Actually, I could probably find Like a Spanish version of it Which sometimes is better Sometimes is much more entertaining. What was the away away goals rule? This is my first time really pan attention JPL like I've watched finals and semi-finals this up in the past But this is my first time actually paying attention to the entire thing For the most part Matt Jude on to 99 Patriots Three-color jumbo patch bears Darnell Mooney number 17 of 25. This is pretty sick dual patch Lamar Jackson Mark Andrews to a 49 sick Lamar patch legendary coach auto Jeff Saturday Colts numbered 30 of 49. I Think it'd be pretty fun if they put him as like a coach auto and one of these as I think holds Two-month coachy coaching legend for sure. Oh, that's a terrible role JPL. That's terrible. Oh Yeah, yeah, that's that's why would they even make that a rule? That's terrible. Oh, that's so clean Signature moves Justin Herbert 16 of 25 Chargers Armando, right? I think you got them all day today Armando with the Chargers nice Big congrats on that one on card great design on this too that is fire and A redemption going to the 49ers rookie patch auto Danny Gray true RPA Danny Gray That's clean as Windex pretty much Yeah, yeah, it is JP, but or they are but not not not. Yeah Not a great rule. I would say God JJ Watts 16 and 25 Cardinals Seahawks Jersey card is a Kurt Warner to 49 that is the The running back Kurt Warner. That's crazy JP. That's wild. Yeah, that is insane Ricky clearly Immaculate Jersey John Matchy the third to 99 Texans I'm sure that caused a bunch of chaos There's a bit of unfairness in that role. I'd say got a Aaron Rogers Nike swoosh three of ten Green Bay Hilton Is this Rogers last year of Green Bay Packers cards? Oh, you're Chelsea fan. You have a tough time But hey got past Dortmund. That's pretty damn good Numbers auto Ronnie lot 33 or 42 Niners. Yeah, I'd be shocked if Rogers didn't go to the Jets right at this point Niners we've got numbers RPA 19 and 20 breeze hall for the Jets That's your Jets do so good in this we've had a lot of breeze hall and a lot of Garrett Wilson today Not a ton of sauce We've hit like a we don't have it hit a sauce auto we've hit some relics I think all right Michael Pittman jr. 10 of 10 Colts Two-color patch card Eagles Dallas Goddard number eight of 99 Dual Jersey Raiders past and present Jerry Rice and Devonte Adams 51 of 99 There we go, I was wondering if we're gonna see Jerry Rice as a raider There he is Yeah, two Raiders legend right there Jerry Rice and Devonte Adams There were a great get a trio of him and rainy moss as well obviously good Numbers RPA Dolphins Eric is who con my numbered 40 of 87 easy Stop please this is cool and on card Roger Stalback auto one of 25 moments auto Cowboys Roger Stalback Stream crash for a second every back looks like we're back And redemption Skymore premium RPA chiefs, I'd be a jumbo patch auto chiefs Steelers TJ Watt number 92 of 99. Yeah, we only got OBS this can I can for like a second and a half and reconnected so we're all right Little full recap still and the recording isn't messed up. So in the YouTube the YouTube upload will be Look totally fine triple Jersey Tim Brown Jerry Rice and Devonte Adams Do the Raiders I'm telling you they're just getting all the Raiders receivers put them on the cards this year At least him round was at least he was there there for like ever There we go triple Jersey Raiders again rookie patch cards in mere white no rookie hat. Yeah, rookie player cap two of fives a mere white Yeah, I'm watching it right now Casper watching a PSG Byron So 49 Falcons auto rookie Tyler Algier 41 of 49 First to me him the next player today First time we've seen a Matt Corral Panthers Ricky shadow box auto one of 49. There you go Panthers Another George Pickens every single case daytime is at a nice George Pickens. This time is 21 of 99 prime patch rookie auto They were probably just a handful last year Vaughn. We're about there. Where are the Jaguars a Jones cards? What about what about that? Well Magda dude the pickings again that auto is not the cleanest one we've seen today either. It's kind of strange Yeah, seems pretty good so far Both teams have had some decent chances Byron does look better Byron definitely more in the front foot here. That's all I can't watch a whole lot obviously I'm breaking but every time I look up It seems like Byron is moving fairly well Niners McCaffrey 28 of 99 again McCaffrey only has base as a Niners in this as a Niner any more Jags Evan Ingram and uh and Z Jones cards Christian Kirk to the standard Jersey JK Dobbins to 49 for the Ravens All you Trevor Lawrence cards. It's like okay. Well, who's he throwing to where are those guys cards at Ravens there Vikings now Jersey card Fran Tarkin 10 to 49 dual patch Titans Derek Henry Jeffrey Simmons 7 to 49 I black RPA Raiders a mere white 76 of 99 the RPA Jets Garrett Wilson 84 of 99 Jets again You go Jets. Give me one sec. We'll do a recap relics first Got Jerry Rice and Devonte Adams Dallas Goddard John Matchy the third Carson Strong Jim Otto Lamar Jackson Mark Andrews Derek Henry Jeffrey Simmons Kurt Warner Tim Brown Jerry Rice Devonte Adams JK Dobbins Fran Tarkin 10 Darnell Mooney John Matchy the third is a mere white Raiders as well Redemption Skymore Chiefs premium patch rookie Otto Niners Danny Gray RPA Rookie eye black autos a mere white Raiders Eric Izucama numbers RPA Dolphins Fran Tarkin 10 Jeff Saturday Matt Corral Tyler Algier Ronnie Lott And a Breeze Hall numbers RPA All right true RPA Jets Breeze Hall to 99 Garrett Wilson RPA Jets to 99 Byron a PSG Prime patch rookie Otto Kenny, uh, not Kenny, but uh, George Pickin Steelers Stovak on card on 25 Cowboys Rogers swooshed to 10 Packers And signature moves Justin Herbert Yeah, that's that's like the new set that they just put in for uh, WWE. Yeah, and that'll do it guys Disgusting that's hockey in a moment