Welcome back. After a brief break, statistics and mathematics is indeed a heady combination for those who are mathematically inclined. And to top it or an icing in the cake is there is lot of application in whatever we are doing. It has a lot of implications in decision making. In order to show to the outside world that our decisions are made in a scientific manner, in an impartial manner we resort to statistics. The decisions are made in a manner which is not arbitrary but that can be defended by sound scientific principles. That is why numerous journal publications are insisting on statistical analysis of the experimental data that are being reported. They do not really care about the scatter or the lack of coincidence of the experimental data but they just want to assure that a proper statistical analysis has been carried out. Now coming back to our lecture, we were talking about joint probability density functions. Without too much of a preamble, let us straight away go to the expected value of a combination of random variables x and y. So let us look at the expected value of x times y which is given by x into y f of x, y xy dx dy. The small x is the representative of capital X and small y is the representative of the random variable y. So the value of x is not specified to be a point value but it is within a certain interval so that the probabilities can be calculated. Here we are putting the limits as minus infinity to plus infinity. If you did not have x and y here, the probability would be such that the integral, multiple integral f of xy dx dy would have been equal to 1. But since you are multiplying it with x and y, the integral need not be 1. It can take any other value. Even if you multiply it with only x into f of xy xy dx dy, as in the case of expected value of x, the integral would not be equal to 1 because you are multiplying it with x. Similarly with y, y into f of xy xy dx dy will not be equal to 1. So what I am trying to say is expected value of x and expected value of y need not be 1 all the time. Now we are talking about covariance represented by COV between the variables x and y. Now to understand covariance, let us think in terms of something we already know. Instead of covariance, if we have only variance and we also have x and x instead of x and y, we have x, x. So the covariance of x, x, there is no sense in talking about the covariance between the same random variable. So x, x would be rather variance. Since we are talking about a single random variable x, it becomes variance and here it would be x-e of x into x-e of x f of xy xy dx dy. So that would be x-e of x whole squared which reminds us of the original definition of the variance for continuous functions, for continuous probability distribution functions. Similarly, covariance of x, y may be defined as x-expected value of x into y-expected value of y f of xy dx dy. This is very interesting. We are drawing back on our knowledge of variance to understand covariance. But since here we are having 2 independent different random variables x and y, we do not call it as variance of x and y. We call it as covariance of x and y. And so we have x-e of x into y-e of y f of xy dx dy. This can be simplified. You will have xy, x-e of y, y-e of x, e of x, e of y. So xy, f of xy dx dy is what you have here. And then you have e of x into e of y and nothing else. This is interesting. What really happened? Expected value of x is a value. Since you are defining expected value of x between the lower limit to the upper limit after the integration has been carried out and the dust has settled, you will have a number. So the expected value of x is a number. Expected value of y is also a number. So with that background, when you multiply e of x into e of y and then f of xy dx dy, e of x and e of y are nothing but constants. And then you have into 1 because the area under the curve or the multiple integral – infinity to plus infinity f of xy dx dy is equal to 1. I would like you or request you to expand this particular expression and carry out the necessary steps to arrive at the final answer. I am deliberately missing out on these steps hoping that you would do them and understand it better. So e of x into e of y times f of xy dx dy after the integration is done. Since integration of f of xy dx dy is equal to 1, you simply have e of x and e of y. So you should have 4 terms. We have accounted for 2 terms. What happened to the remaining 2 terms? It is very interesting. If you look at it, x into e of y, f of xy dx dy will become expected value of y into x of f of xy dx dy. So that would have become e of x into e of y. And this combination multiplied by this function would lead to again e of x into e of y. So you have x into – e of y that is a negative y into – of e of x which is again a negative. So you have – 2 e of x e of y and then you have 1 plus e of x into e of y and so you have – e of x into e of y. So the covariance between x and y finally is e of xy – e of x into e of y. So rather than leaving the derivation to yourself, I thought I will use the board for a change and do the steps myself. Hopefully I have not made any mistakes here. So what we do here is x – e of x into y – e of y f of xy dx dy. So I am multiplying first these 2 terms or these 2 expressions in the 2 brackets xy – x e of y – y e of x plus e of x into e of y f of xy xy dx dy. Even though in the slide I have put – infinity to plus infinity, x can vary from – infinity to plus infinity – infinity to plus infinity for y also. As a general representation, it has been put as – infinity to plus infinity in the slide. So now we can multiply each and every term in the bracket with f of xy dx dy. We get this term and then we know that e of y is a constant. It can be taken outside the integral. So we have x into f of xy dx dy. Similarly, e of x is a constant. So it can be taken outside the integral – infinity to plus infinity – infinity to plus infinity. Here you will have y into f of xy dx dy and this is interesting. These 2 are constants. So you get e of x into e of y into f of xy dx dy. So this is equal to 1. By definition, this becomes e of xy. This becomes e of y and this becomes e of x. So we have e of, this is e of xy, e of xy and this is e of y into e of x, e of y into e of x into e of y. So this becomes – 2 e x e y and this is e of x into e of y. Once you subtract e of x into e of y from – 2 e of x into e of y, you get – e of x into e of y. So you have e of xy – e of x into e of y. So this completes the derivation even though it looks very cluttered and highly mathematical. It is basically very simple. This is a very important result which we will be using pretty frequently. Those of you who are curious may wonder what will happen to the covariance between x and y if x and y are independent. If x and y are independent, they may not have a combined action, a similar action. One variable determining the other variable or influencing the other variable. So intuitively you will have to question what will be the covariance if x and y are independent. What will be the value? Will it be – infinity, 0, 1 or plus infinity and can that be proved from e of xy – e of x into e of y? If x and y are independent, what will happen to e of xy? Will e of xy be e of x into e of y? So please look at this. Look at the covariance between x and y. If x and y are independent, what will happen to the covariance and what would happen to e of xy and what will be the relation between e of xy to e of x into e of y? So to save you the long wait, I am giving you the answers right away. If x and y are independent, it can be shown that e of xy is equal to e of x into e of y and the covariance becomes 0 between x and y random variables. Since x and y are independent, they behave independent of each other, one does not depend on the other. The covariance between x and y is also denoted by sigma xy. Now let us assume that we have the distributions being normal or Gaussian. Let us say that we have 2 independent normal distributions. It can be shown that the linear combination of the random variables based on these 2 populations will also be normal. If there are 2 independent normal distributions, important thing to note here are independency and normalcy okay. So if there are 2 independent normal distributions, the linear combinations of the random variables based on these 2 populations will also be normal. When 2 random variables are independent, their covariance is 0. So what is the significance of covariance? Covariance of 2 random variables x and y indicates how x and y vary with respect to each other. It is a measure of the linear relationship between the variables. So the correlation between variables x and y denoted by rho xy is defined as covariance between x and y divided by square root of the variance of x into variance of y which is sigma xy divided by sigma x into sigma y right. So what we have understood is if the 2 random variables are independent, the covariance vanishes or becomes 0. Now we are going to talk about 2 independent normal distributions. So if you combine 2 normal distributions that the resulting distribution is also normal. If the parameters of the 2 normal distributions are mu1 sigma1 squared and mu2 sigma2 squared, what are the parameters of the resulting normal distribution arising out of the linear combination of the 2? So when you are having 2 normal distributions and you are combining them, it also becomes a normal distribution. What are their properties? The properties of the original normal distributions where mu1 sigma1 squared mu2 sigma2 squared. So the resulting normal distribution what mean and what variance would it have? That is the question we have to answer now. So we look at a general case involving n independent random variables. We will assume that all of them have come from populations that have the same mean mu and variance sigma squared. So we are talking about n independent random variables and all of them have come from identical populations of the same mean mu and same variance sigma squared. So let us say that the variance of the random variable x is v of x and is equal to sigma squared. So x is taken out of a probability distribution function, a normal probability distribution function and the variance of this random variable x is sigma squared. So what would be the variance of x bar? x bar we know is defined as x1 plus x2 plus so on to xn whole divided by n. Sigma x bar squared will be for independent random variables x1 x2 so on to xn. Simply variance of x1 by n plus variance of x2 by n plus so on to variance of xn by n. So we have already seen one of the example sets. If I remember the first example set, if you take a variance of a quantity x1 divided by n, you cannot put n directly outside. It will be 1 by n squared and then variance of x1 will be sigma squared and variance of x2 by n will be again 1 by n squared into sigma squared because x1 and x2 have come from identical distributions of the same mean mu and same variance sigma squared. So we have so on to xn will also be represented by sigma squared by n squared. Variance of xn by n will be represented by sigma squared by n squared. So when you add up all these things, you have n entities n sigma squared by n squared which is nothing but sigma squared by n. This is a very important result. What is the implication or meaning of this result? Don't look at the mathematics.  You are having a sample and that sample is having a mean x bar. If I take many such samples, not all of them would have the same sample mean, they will not have the same sample mean. So there is also a distribution of the sample means. Different samples will have different means and so there will be distribution of the sample means. It is hardly surprising because x bar is also a random variable and it is also associated with the probability distribution. We are talking about a distribution of the sample means. What is the variance of that distribution? If x, the random variable x came from a population of variance sigma squared, what is variance of x bar? From now on, we will be shifting to a slightly higher level. Instead of talking about x, we will be talking more about x bar. We know that x is a random variable which came from a population of mean mu and variance sigma squared. It might have been a normal distribution or a not normal distribution but properties are mean and variance mu and sigma squared respectively. Now we are shifting gears or moving to a slightly higher level. We are now talking instead of x, we are talking about x bar. x bar is also a random variable. It will also have its own mean. It will also have its own variance because it has a probability distribution. There is a distribution of the sample means. Hence that distribution will have a variance. It will also have a mean. What is the variance of the distribution of sample means? The variance of distribution of sample means is not sigma squared but sigma squared by n. Variance means spread. If I am taking a large number of samples, then there will be a distribution of the sample means. And that spread, if I want to curtail that spread, I do not want that much uncertainty. I want the values to be precise. What should I do? I will increase the sample size n. If I increase the sample size n, you can see that the variance of x bar will reduce okay. So the spread of the different possible sample means will reduce if I increase the sample size. So lot of physical basis is there in this seemingly simple derivation. We have taken a linear combination of random variables which is what we stated at the outset and we try to find its variance. And we wrote x bar as x1 plus x2 plus so on to xn and then divide by n. It looks very simple. It looks too easy to be true. Variance is an operator. If you consider as an operator and we are operating it on a combination or a function of random variables, it appears to be linear operator because it is equal to x1 by n plus x2 by n plus so on to xn by n okay. It looks very simple but this is only applicable when the random variables were independent of each other. If they had not been independent of each other, what would have happened? That would lead to again cluttering the slide or the board with more of these multiple integrals. But all of you may not have the time or patience to do this integration. I am sure there will be many of you who would like to carry out the integrations on paper using pencil and paper. But it is not necessary to do all those to understand the simple basic concepts. If the random variables are independent, this variance of x bar can be represented by v of x1 by n plus v of x2 by n plus so on to v of xn by n and that becomes sigma squared by n eventually okay. The variance of the distribution of sample means about mu is sigma squared by n. So, the question is where did this mu come from okay. We are talking about variance of x bar. You know that expected value of x, x is coming from a probability distribution. Expected value of x is equal to mu. What is expected value of x bar? We will be looking at the derivation also in one of the slides. But I request you to write down expected value of x bar and try to see what would be the resulting value okay. Expected value of x bar would be expected value of x1 plus x2 plus so on to xn by n and what is that value going to be okay. I will just use the board again. So, we have been looking at variance of x bar. Variance of x bar was x1 plus x2 plus so on to xn by n. Expected value of x bar would be expected value of x1 plus x2 plus so on to xn by n. So, this will be expected value of x1 by n plus expected value of x2 by n plus so on to expected value of xn by n. So, unlike the variance where when you take it outside the bracket it became 1 by n squared it will become 1 by n. Similarly, for all other expected values and you will have expected value of x1 plus expected value of x2 plus so on to expected value of xn okay. This is expected value of x bar. What this means is all these random variables are coming from identical distributions of mean mu and variance sigma squared. So, we have 1 by n into mu plus mu plus so on to mu. Expected value of x bar is also equal to mu. A very interesting result and much more simpler than the multiple integrals we did earlier and also simpler than the variance of x bar. So, it indicates that the variance of the distribution of the sample means about mu okay is sigma squared by n. The mean of the random variable x probability distribution function is mu. The mean of the distribution of the sampling means is also mu okay. The variance of the random variable x's probability distribution function is sigma squared. However, the variance of the sampling distribution of means is not sigma squared but sigma squared by n. So, these are very important results and we will be applying them in many problems from now on. I told you that it is not a simple linear operator. There is something more involved here. So, variance of x bar is equal to expected value of x bar minus expected value of x bar squared okay. There are two expectations but one expectation is within the bracket and another expectation is outside the bracket. I hope I am not expecting too much out of your mathematical knowledge. These are pretty straightforward and terminology. variance of x bar is equal to the expected value of any variable about the mean. So, now putting it in terms of the original probability distribution function, multiple distribution or joint probability distribution, we have x bar minus expected value of x bar whole squared into this form. So, when you look at this, it is a matter of expanding the terms inside the brackets or parenthesis, x bar becomes x1 plus x2 plus so on to xn by n and since you are having a squared term that would become 1 by n squared. So, we write x1 plus x2 plus so on to xn minus e of x1 plus x2 plus so on to xn. This e of x bar also had a 1 by n term x bar also had a 1 by n term and when you are squaring it, it became 1 by n squared and that was removed outside the integral. So, you have this form just more convenient to handle and then you have this probability distribution function for x1 to xn. I am as of now not assuming independence between the random variables. This can be written as 1 by n squared into x1 plus so on to xn minus e of x1 plus so on to xn whole squared f of x1 to xn, the random variables x1 to xn dx1 to dxn. What we do here is, we will collect individual group terms squared plus the binary product of the individual group terms. So, I am having this x1 minus e of x1. I am just simplifying this term. I am collecting terms of the deviations. So, x1 minus e of x1 x2 minus e of x2 xn minus e of xn within the bracketed term that is eventually squared. So, you have x1 minus e of x1 deviation of the first random variable about its mean, the second deviation, the nth deviation and so on into the joint probability distribution function. So, when you do that, after taking the square, you will have the squared of the deviations and also the cross product of the deviations. This is very important. You are having the squared of the deviations and this cross product of the deviations. The squared of the deviation times the probability density function will represent the variance and the cross product term times the probability density function would represent the covariance. So we get V of x bar equals V of x1 plus V of x2 plus so on to V of xn plus twice the sum of all the covariance terms between xi and xj okay. This may be a bit difficult for some people to follow. You may carry out the same derivation with 2 random variables x1 and x2 and you can see that it will reduce to variance of x1 plus variance of x2 plus 2 times the covariance between x1 and x2. When you have more random variables it is a simple extension and you will get the sum of the variances plus the sum of the cross product terms or the sum of the covariances divided by n squared. If the covariance between xi and xj was 0 because xi and xj was where independent random variables and if all the random variables were independent of each other so that any combination between them will lead to a 0 covariance then the entire sum of cross product terms or the covariance terms will vanish and you will have V of x1 plus V of x2 plus V of xn by n squared. So much of mathematical background is behind the simple expression for variance of x bar okay. Suppose you had difference of random variables V of x1 minus x2 then the covariance term here would have a negative coefficient okay but the actual variance terms would all be having positive coefficients or positive unity in this case. So if you had V of x1 minus x2 it will be variance of x1 plus variance of x2 not minus variance of x2 but plus variance of x2 okay. The negative sign corresponding to that x1 minus x2 would have come in the coefficient of the covariance okay. This is very important and follows from rigorous mathematical background. So if the population distribution is normal with mean mu and variance sigma squared then the sampling distribution is also normal with mean mu and variance sigma squared by n. We assume that the random sample entities or the random variables constituting the random sample are independent of one another. Now we have been talking about a lot of variances okay. So we need to be sure that we have understood them properly. What is the difference between sample variance s squared and variance of x bar? The sample variance is the variance of the sample you have taken okay and that sample is averaged to give the sample mean x bar okay. S squared is the variance of the sample okay and variance of x bar is the variance of the sample mean okay. S squared refers to a specific sample. Variance of x bar refers to the many different samples that have been taken okay. So each sample would have its own sample mean. Each sample mean may be different from one another and hence v of x bar denotes the variability of the sample mean okay. S squared is a random variable and is an estimator of the population variance sigma squared. We do not know about the population variance sigma squared. So we take the sample find its variance because a sample will have x1, x2 so on to xn. So we take the values of the random variables and find the s squared and the sample variance is based on a single random sample of size n drawn from the population. It is defined as for that particular sample i equals 1 to n xi-x bar whole squared by n-1 okay. Now when you are talking about sample mean, we add up all the random variables and then divided by the sample size to get x bar. Now if you draw many samples from the population, you calculate the sample mean for each of those samples using the entities of those samples using the same formula x1 plus x2 so on to xn by n okay. So each sample will be calculated for its sample mean using the same formula but each sample will involve its own entities okay. So you are calculating sample mean for the first sample as that first sample's entities x1 plus x2 plus so on to xn divided by n. The second sample will have again n entities and using those n entities, you will use the same formula to find the second sample mean. The first sample mean and the second sample mean need not be the same. Similarly if you draw many such samples, those sample means will not be the same. So there will be a distribution. So the variance of that distribution of sample means is denoted by V of x bar or sigma x bar squared okay. So we have now distinguished between the sample variance s squared and the variance of the distribution of sample means variance of x bar or sigma x bar squared. How did that come about? We have already seen. We assume that the sample means are comprising of entities that were independent of each other and they were identically distributed. So taking a particular sample mean, we saw that variance of x bar was defined as 1 by n squared into variance of x1 plus variance of x2 plus so on to variance of xn plus the sum of the covariances between xi and xj taken and turned okay. So since the random variables were independent, all the random variables were independent of each other. All the covariances disappeared and you had variance of x bar as sigma V of xi by n squared. And we also made the further assumption that all these entities have the same variance. So sigma 1 squared plus sigma 2 squared plus so on to sigma n squared will become n sigma squared by n squared or sigma squared by n okay. So finally to interpret variance of x bar, many random samples may have been drawn from a population. Each of them may have a different sample mean. So there will be distribution of sample means and the variance of this distribution is V of x bar. V of x bar is given by sigma squared by n. Larger the sample size, smaller would be the variance of x bar. So it means that if you take large enough sample, there will be less difference between the different samples that you have taken, different samples that you have taken. So the distribution of sample means will become more narrow if you increase the sample size. We also are now defining another term called as statistics. Any function of the random variables x1 to xn is termed as a statistic. Since x bar and s squared are taken from the sample random variables by using a mathematical definition for each case, they are referred to as statistics. Since they are also random variables, they have their probability distributions associated with them. For the time being, our focus is on the sampling distribution of the sample mean x bar okay. Later on, we will be looking at the distribution of the sample variance s squared. Each is described in terms of unique probability distribution functions which constitutes the fascinating variety in the field of statistical analysis. So this sort of concludes our discussion on the distribution of sample means. We have seen what is meant by a sample, what is to be done in order to make the sample random and what are the properties of the random sample. And if there are many random variables in the random sample, they have to be considered mathematically together in terms of a joint probability distribution function. Fortunately, in our case, the random variables were independent. So some simplification was possible to the joint probability distribution multiple integration. And we were able to find that the expected value of the sample is mu and the variance of the sample is sigma squared by n. Here the sample size n also plays a very important role in determining the shape of the distribution. So we will conclude at this point and we will proceed to the next phase in a very short period of time. Thank you.


Thanks to Ukraine's People's Satellite, hundreds of Russian equipment were destroyed. The ISA spacecraft purchased with the donations from Ukrainians has helped detect and destroy thousands of pieces of Russian military equipment in five months of use. About it announced Defence Intelligence of Ukraine. Ukrainian Defence Intelligence started using the People's Satellite on 24 September 2022. Since then, the security and defence forces of Ukraine have been receiving necessary data from space daily. In five months of using ISA, members of Ukrainian Defence Intelligence have conducted space radar reconnaissance in almost 1,000 areas of deployment of military units of the aggressor state in the temporarily occupied territories and other territories of interest to the armed forces of Ukraine. During this time, the resources of the spacecraft have allowed the armed forces of Ukraine to detect 360 tents in areas where the Russian occupying army was deployed, as well as 7,321 pieces of Russian military and special equipment. Specifically, 45 planes, 27 helicopters, 6 Iskandar mobile short-range ballistic missile systems, 36 S-300 anti-aircraft systems, 12 Pantsir S-1 missile systems, 11 radar stations, 10 pontoon bridges. Thanks to the capabilities of ISA, a big part of this list has been destroyed and included in the daily reports from the General Staff of the Armed Forces of Ukraine.


From Hollywood. It's time now for Edmund O'Brien as Johnny dollar Calling back. Oh, yeah Your reservation for Bermuda has just been confirmed pan American flight number 134 You'll leave LaGuardia at 10 30 a.m. Arrived Kindlefield Bermuda to 30 p.m. Got it We'll send the tickets right over. It's been a pleasure to serve you sir And I hope you have an enjoyable stay in Bermuda. Is it a vacation? Well hardly I'm going down there to look up a dead man Edmund O'Brien in another transcribed adventure of the man with the action-packed expense account America's fabulous freelance insurance investigator yours truly Johnny dollar Expense account submitted by a special investigator Johnny dollar to tri-state life insurance company attention Leland scoff chief adjuster The following is an accounting of my expenditures during investigation of the Earl Chadwick matter Expense account item 1 a dollar 80 cab fare to your Hartford office The man has been seen alive dollar. I never was satisfied that he was dead His boat a small cruiser was found wrecked. You know, but never a body. How long ago was that little over four years ago 1945? He was declared dead in 1947 in appellate court and we were forced to meet the claim of his widow or his wife and accomplices It might seem now Go ahead Here's the lady that saw and spoke to him. This is Marshall. This is mr. Dollar. How do you do this Marshall now? I want you to tell mr. Dollar what you told me Mrs. Marshall if you will well My husband and I had been in Bermuda for three days. Mrs. Marshall explained that you knew Earl Chadwick before. Oh, yes Yes, we knew him not too well. Thank heaven But well enough to be pointed out as friends of that embezzler, you know how people are embezzler Mrs. Marshall Oh, yes, there was a tendon theft He worked at the Monticello loan company in New York City $30,000 disappeared at the same time he did Police theory was that he wrecked his boat while attempting to leave with the money Now Mrs. Marshall how you happen to see we've been there three days and that night We went to this nightclub in Hamilton and slumming so to speak It's called the Port of Castile on the waterfront There's been a number of years mind you and Chadwick was much thinner, but I recognized him He was seated with some sailors and I said Jerome doesn't that look like her and then you spoke to him. What else could I do? I was dying of curiosity when he got up to leave. I met him and said aren't you well Chadwick? He denied it of course, but being that close. I'm positive that it was What did he say did he give you a name? No, no, but I found out I thought I was quite within my rights and asking a few questions the name. He's using is George Brewster Well dollar What about Chadwick's wife? What happened to her? She remarried one of his business associates Harold Anderson him I had the girls draw up a complete record on the case Photographs police reports everything you'll need the wife's address is there in Queens. I think all right mr. Scarf I'll do what I can Expense account item to $250 plane ticket and miscellaneous expenses between Hartford and Bermuda. I drew an aisle Seat and one of the worst hazards of air travel or any other kind of travel I'll tell you something phase to study these places before you go to them. I've been out there before Nothing teaches life experience But before my first trip I knew more about Bermuda than lots of the folks that live there. They well, that's very interesting Yeah, yes, sir Quite a history spoiled now though people aren't worth anything anymore No, let's spoil them tourists. Hmm.  I don't want to be a wet blanket. You understand. Oh, yeah But keep an eye on your wallet. They'll strip you if you give them a chance My business is farm tools. What's yours? My name is Dalla is my credentials. I'd like to see the chief constable Yes, sir. Mr. Dollar to see you sir an insurance investigator from the States Right, sir and that door mr. Dollar. Thank you Mr. Dollar your company cable that you were coming sit down. Thank you. Well now You're here to look into the affairs of one George Brewster. What's it been up to? I'm not sure he's been up to anything yet According to a witness he answers the description of a man who disappeared from New York a few years ago with $30,000 He was declared dead and the company that hired me paid off an $80,000 insurance claim to his wife I see quite a valuable chap. Yeah, if he is the chap But what about this Brewster? Do you people know him? We acquainted ourselves with him after the cable arrived nothing against him lives a rather rum life doesn't seem to have much Are his papers in order passport visas? I Trust that he wouldn't be here if they were not Like any other paradise mr. Dollar a Bermuda is forced to accept the existence of a certain percentage of misplaced or lost persons on its outskirts That's what they are. They here's the address Thank you at the lower end of King George Road. You wish transportation. No, no don't bother the walk will do me good I decided against the King George Road address instead. I returned to my hotel Memorized the photographs of Earl Chadwick Subtracting a little weight from the somewhat flabby face and that night I found myself a table near the door at the port of Castile I Sat there nursing a minimum of fouled drinks. It was 10 o'clock before he came in and found standing space at the bar George Brewster, huh or Earl Chadwick? What's the matter with you? What is this? I'm curious too. How about coming over to my table?  I'm working for tri-state life insurance company What does that mean ensure a man and paid off to his wife now now they are insurers dead He belongs to that other name you threw at me. What was it Chadwick Earl Chadwick, and I must look like him Here's a snapshot He's fatter, but it's pretty close at that. You know about a week ago some crazy old name I never saw before called me some other name it might have been Chadwick I thought she'd drunk over her quota. She was an old friend of Chadwick's She swears she'd recognize him if if she saw him and she swears she saw it weird isn't it? I suppose it happens more often than we know about What do you want my papers and stuff they might help sure I'll write down my address Come on out anytime tomorrow There you are. Thank you. I should recover from these drinks by noon.  I'm Johnny dollar Is George here? No, he had a leave He said you could come in How long have you known him? Two years last month You know where he came from never asked me where I came from This guy looks like Yet a wife. Yeah, I want to take some of his personal things into town or check his prints against this passport Shaving brush if he uses run tubes jars anything you think he's the guy I'll have to find out Oh You told me you were going the prince would check against the passport, but it wouldn't make any difference now that it started Why stretch it out? Why not make it easy George? No Earl? I'd almost forgotten Earl Where can we talk? I've got a hotel room Statement he made filled in most of the blanks in the case one his wife was to have met him in Mexico City That hadn't to most of the stolen funds had gone to his wife to keep her going until she collected the insurance So she got married. I didn't know that she told me to wait and I did Grace married We can leave for the state Well, oh I can be ready anytime you say all I have to do is pack a few things and say goodbye to Fran Expense account item three space for two on New York bound plane Chadwick was a hard man to figure out, but one thing I did realize Now that he'd started he was almost happy to be going back to the people he'd left We arrived in the evening in the next morning I was told when I telephoned that Mrs. Grace Chadwick Anderson and her husband were at home and would receive Good morning. I hello Grace Harold I think you're pardoned. Oh, I understand Harold This must be the man that Mrs. Marshall phoned about you know the one in Bermuda. Oh come now Grace That's no good. Who are you anyway? Mr. Dollar for what purpose did you and this man come here?  Yes, but that's all what what do you have in mind? Mr.  Get him out of here? Why? Why not talk over all time great wait a minute? All right, Mrs. Anderson mr. Anderson I'm sorry. I've taken up your time come on dollar. What's the matter you too come on Who do you think I am I? Asked you who do you think I am that doesn't count you're legally dead What about your parents they're dead, but I have friends or people that knew me and oh good if your wife won't identify you They're no good. You worked for a loan company. They must have your prince I took them from the files and destroyed them when I left. How are your teeth, right teeth? Who was your dentist here in town? Dr. a field it's been so long dr. Homerfield Uh Drake professional building Manhattan He'll still have your x-rays on file. They're as good as fingerprints go there this morning Don't use your name give him your other name George Brewster have a new set of x-rays taken. I'll do the rest all right hold it And look, I don't have to hire somebody to follow you do I know? Oh, no not after I've seen them You don't have to worry about my going any place Expense account item for twenty five dollars services of a private detective Assignment tailing Earl Chadwick and or George Brewster at one o'clock He had left the dentist's office and gone to his hotel room at three He was still there and at 430 I arrived in the office of dr. Homerfield Brewster Yes, yes, his x-rays have gone through. They're on the clamps. Don't don't touch them, please What is your interest police identification? Oh? Yes, yes, we'll always happy to cooperate right now How about digging in your files for the x-rays on a patient named Chadwick Earl Chadwick? Be glad to Oh M Chadwick, is that your man? That's the name 1945 he should have been in for hygiene those pictures. How do they compare with this new set Brewster? Well, let's have a look There's malocclusion and lower by cusp and Impacted third molar and I erosion in labor interesting You mean they're the same and both sets of pictures. No, no, no, no, definitely not. Oh But a man's mouth could change since 1945 good man Yes, it could especially with neglect But that would never cause a man to grow new teeth now you see here Brewster has one more incisor than Chadwick the whole character of the mouth is different. I see yeah I say it's different or I definitely by these two men would not look even faintly alike In just a moment. We will return to the second act of yours truly Johnny dollar, but first Down the old ox road learned to croon straight from the shoulder Milestones and popular American music Milestones in the career of one of America's favorite troubadours Bing Crosby This Wednesday night over most of these same CBS stations You're invited to hear the Bing Crosby show Bing Crosby with the music of John Scott Trotter with the Rhythm Air is with Ken Carpenter Here's the show designed for the whole family a pleasant and diverting mixture of music and merriment Guided by the one and only Bing Crosby Planned now to hear the Bing Crosby show this Wednesday night on CBS And now with our star Edmund O'Brien we return to the second act of yours truly Johnny dollar Look Dr. Field these x-rays labeled Earl Chadwick could they be miss filed could they be under the wrong name miss filed Definitely not my assistant has been with me for ten years never made a mistake yet Well then could anyone else have gotten in here and planted a different set under that name But why I would realize the difference the moment I looked into the mouth that erosion in lay alone. Yeah Look your office has it been broken into yeah a long time ago for narcotics How long ago six seven years ago during the war but not since then I've missed nothing The janitor the nightmare is he ever key? No, no, it's cleaned in the evening just before I leave the robberies out of the question Just what is your problem, mr. Dollar? If I wanted to plan some x-rays in a file, where could I get some? Well, I never thought of it Where would I go would you give me son? Oh, no, definitely not that would be most unethical one unless of course You were a patient of mine and the x-rays were of your own mouth. Thank you doctor. I think that's what I wanted to hear you say Before dark I made two more stops Searching for something to help me prove that Earl Chadwick was alive if he was The Hall of Records had nothing but a couple of certificates on one recorded his birth the other recorded his death I checked the wanted file at police headquarters. They had checked him out in 47 when the court had pronounced him dead On my way out of there. I made two phone calls. The second was to the detective. I'd hired Landro, what are you doing in your office? Did you lose him? I get tired. He was on to me dollar He got into the crowds at Macy's. I put the houseman at his hotel on it. He's watching his door I just found his room. He's not there. What's he been up to he left the hotel at 3 18 and took a cab over the What address a pawn shop Johnny Nice going Landro if you decide to change over to stopping traffic at school crossings use me as a reference Where's your husband miss Anderson? He's here, but I want to talk to you both Where is he what is it Grace oh? It's you again. That's right forced his way into the house make him get out Harold I will if I have to now look here. I don't know what that imposter has told you and I don't care If you choose to believe his lies, that's your business and a sorry business It is but I will not allow my wife on my home to be upset by his schemes any longer. Are you through no not quite That's obvious to us if it's not to you that this man learned of the unexplained details surrounding Earl's death And is attempting to use this vague resemblance to his advantage Now extortionist land and prison mr. Dollar and the only reason I haven't turned to the police before this is that we Want to escape the notoriety of having passed tragedy is lived again. He bought a gun this afternoon That makes him look like the double-crossed husband, doesn't it? Man's a maniac I'm going to ask for police protection. Where is he who? This man, do you know where he is? I found out he bought a gun. I was afraid he was coming here to use it I can't believe this is happening grace, please Why why why would he harm us? He doesn't know us and we don't know him He bought the gun to convince you dollar. He knows a lot about you Anderson He knows you were Chadwick's immediate superior in the loan company before he disappeared Harold it It couldn't be could it grace been a long time Maybe some disease could change a person that much, but he would have contacted grace Earl is dead. How did this man learn so much about us as far as I can see he's made only one mistake The size of the theft he says he stole ten thousand according to the record thirty thousand was missing Of course, it's possible that it isn't a mistake that somebody in the firm who knew what his plan was Picked up the odd twenty thousand and put it on Chadwick's account. Mr. Dollar I have one thing to say to you before you leave Earl Chadwick is dead You're so right and that's what troubles me a Legally dead man running around loose with a gun makes an interesting situation. Do you ever think of that? Who would the police look for? I'm going to my hotel in case you want to phone in your answer Where have you been Chadwick right here the maid let me in What's the idea? I was scared somebody was following me. I got the feeling they hired somebody to get rid of me No, why not they haven't thought of that yet. Give me the gun. I need it. Come on. Where is it? Never mind get away from me. Come on. Where are you carrying? How did you know I had it what were you gonna do with it?  How should I know what's going on in that head of yours? Why'd you come back then just to get things straightened out? You wouldn't have had to I haven't found a way to prove who you are Oh, I knew I didn't have to come back But everything was stagnant being George Brewster was dull I thought that's what I wanted a new identity even without grace But I guess nobody's ever satisfied and when you have a choice of who you want to be then it's really hard What about the x-rays? Oh good the set under Chadwick didn't match the one you had taken today They had to they made a switch with somebody else's probably Anderson's an easy office to enter Probably hired a cat burglar Nothing at the Hall of Records. Nothing at police headquarters. You're dead. What did the police say? I didn't talk to them. Why should I the case is closed?  Yeah No, yeah, sorry I blew up How is it? Oh, it's a mess. I'm not getting any place the only proof I can find is proof that he's dead Maybe you should stay there. Yeah, I'm getting ideas myself Police checked in 47 they lost look I'm gonna have to dummy up something I don't want you to violate any trade secrets, but do you know a good forger? It'll be practically legal all I need is a driver's license When tonight it'll cost well, I'm working for a wealthy company There's more to Landro. How about meeting us in your office in 45 minutes? Spencer count item five five hundred dollars one bogus 1947 driver's license complete with Chadwick's thumbprint by 10 p.m. We were back in Landro's office Johnny how desperate is this Anderson desperate enough to welcome a nice fast deal Don't quote a price unless you have to just get him down here Why anybody goes through all this to make prison prison come on Landro get on the phone There's the number You're my client Mr. Harold Anderson I'll be blunt. This is blackmail. I'm calling in the interests of Earl Chadwick No, he isn't he's alive But I do have proof a driver's license. He took out just before he disappeared as a sort of a double check on the past You'll believe it when you see it. It's for sale He doesn't want to go to prison any more than you do but he needs money. I Said you'd believe it when you saw it. I Think it'll be worth a trip over here We'll talk price them We meet here number four six five tight building 7th Avenue It's no bluff Nobody knows about it. I'll be alone He doesn't believe it only be here. He said 45 minutes good now Don't make the price too high set up a meeting with him tomorrow and we'll have the police here. Well step forth Lazarus Empty the ashtray's Landro looks like three men have been here Drive to 1130 Chadwick and I in an adjoining room with the door cracked watched his wary entrance The name is on the door You work under a license issue by the state of New York sometimes But the license isn't important tonight You won't make any trouble sit down I'll handle Here it is. I just look Name serial number a date a signature and a thumb print Where is he he'll phone me in the morning, but where's the man from the insurance company looking for Chadwick? He doesn't know about this yet Why why is he waiting this long? He didn't know everything that had happened you and his wife the money you made on him That's the price. Well as he put it to me It ought to be figured from the 20 grand you took and the advance you've made in the company the last few years How much he'd like to start at 15,000 it would take a while 5,000 tomorrow say around noon The other 10 within a week. That's when you get the license Well, it would have to be later than noon tomorrow, but I brought 1,500 with me. That's a deal All right I'll give it to you. Hey watch it. Don't do it Anderson wait Landro down Landro I'm all right Chadwick Chadwick Chadwick Pulse pull his collar down Nothing know what your company can do about it now Both mr. Mrs. Anderson gave statements to the police that same night Confessing their contribution to the original crime You'll have a hard time prying Harold Anderson loose from the clutches of the state which is working on a murder indictment for him About the wife grace. I don't know If she's not found guilty as an accessory I'd be happy to appear as a witness if she's brought to trial on fraud charges As for my part in it I'm not proud of myself, but I was hired to find a dead man and I finally found one just before he lived Expense account total 1575 dollars and 30 cents yours truly Johnny dollar truly Johnny dollars stars Edmund O'Brien in the title role and Is written by gill doubt and David Ellis with music composed and conducted by Leith Stevens? Edmund O'Brien can soon be seen starring in the Columbia Pictures production the Los Angeles story Featured in tonight's cast where Lillian by F. Walter Burke, Virginia Greg John Boehner Ben right Tudor Owen and Ted Osborne Yours truly Johnny dollar is produced and directed by Jaime del Valle Join us again next week at the same time when from Hollywood Edmund O'Brien returns in another transcribed adventure of yours truly Johnny dollar every Wednesday night CBS brings you Groucho Marx with his brilliant quiz you bet your life It's one of the brightest most spontaneous most genuinely funny shows on the air So be listening this Wednesday night on most of these same CBS stations for you bet your life starring Groucho Marx Stay tuned now for the adventures of Philip Marlowe which follow over most of these same CBS stations This is CBS the Columbia broadcasting system


Again when you got three activities kind of in one going on it just it just makes for a better use of time I think. One of the things right off the bat and watching Terry it's just his demeanor with the players, it's you know, it's kind of like, you know, you're, you know, he just he just gets no he cares about him. He's good at explaining things. And so when I watched that you know the only, you know, I watch it in the only couple things one thing I would add probably or change and not to say that, you know, you know, the last service to me could possibly be similar to the one from the from the right side. Maybe the player has the ball goes beat somebody now and plays the most devastationary ball and also give them maybe more time to prepare their runs and I think that was one of the key things that Terry pointed out was, you know, they're all in there standing in there. And he talked about them creating space so they can attack that space and attack that ball.


Okay, that's how we open this. B.A.S.H. Hoo! Oh my god. He just pooped on my screen. What the?  And now he took my cursor. Dude, bring it back. What is he doing? I can't move it. Oh my gosh. What's up YouTube? RealisticGaming here. And today we are on this door is not dead remastered. As you can hear, the door music is like corrupted and whatnot.  It's actually like an app where it's just a random, it spawns a random goose on your screen and he just bugs you the entire time while you're on the computer. I don't know, I thought it would have been pretty cool and here we have him today. And what? He's bringing something out of the screen. What? What is that? It says... Dude, what is this? Mess with the hunk, you get the bonk. What? Let's go ahead and begin with this. Dora is not dead. Oh my God, that goose is gonna distract me. Okay, find a way out. Okay, oh wait, okay this way. Hello Dora, where is Dora? Okay, there's an arrow pointing this way. There has to be some sort of hammer so we can break down those planks, which I cannot find. Okay, red arrow, I guess we just keep following the... Okay, that's blood. That's not even an arrow anymore. Okay, find a key, a gate. This looks like my way out. Peace was never an option, the goose me. Okay, so let's go find a... Let's go find a key to escape this place. Dude, it's so dark and creepy out here. Oh my gosh, what is this place to begin with? Like some abandoned factory of some sort. Okay, where the heck am I gonna find the key out here? Come on man, help me out here goose. Okay, that man's not helping me out. He's distracting me. Wait, what was that? Yo Dora, what is wrong with Dora? Oh my God, yo, she's missing an eyeball. Okay, we gotta go, go, do not run towards Dora. We gotta run away from Dora.  Can I just like kick her, punt her like a football? Oh no, was that Dora? Dude, that is clearly Dora, do you not see? That is Dora. Okay, this is not good. Why, we're trapped in here. We're trapped in here, go, go around. Oh my God, close the door. Can I just throw her in the trash can bro? Okay, um, we're supposed to find the key. Where the heck am I gonna find the key here? Key inside, find the hammer to remove nails. Great, so now we gotta find the hammer to remove those nails out of that door. Okay, it has to be here. I know it has to be here. Okay, there's nothing here, great.  Just let me play the game. No, that was boots, it was like the ghost of boots. Okay, there has to be something here. What is that, there's a fire? Oh, it's a car upside down that crashed and now it's on fire. Okay, that makes a lot of sense. Okay, what the heck am I supposed to do, man?  Okay, oh, what is that?  Okay, man. Well, thank you for letting me know what you're capable of, Dora. You know what, Dora? I am capable of doing some pretty horrible things myself, so... I would watch it if you wanted to threaten people. Okay, let's keep going this way. Oh my... Game over, your legs are mine. Oh, we're supposed to be Swiper the Fox. Okay, I get it. Hey, this dude just took my cursor, man. I'm trying to get rid of all these windows he's leaving here. Okay, so we're playing as Swiper, no Swiper the Fox, and we just got our guts, our legs ripped off our body. What the... What is this? A room of mannequins? Okay, this is kind of creepy. How did she come from there? And there was a... Oh, great, we're stuck. And there was a Dora hanging on the wall there. Goose, leave me alone right now, Goose. This is not the time. Oh my gosh, okay. There has to be a hammer around here somewhere.  The lights are flickering. What is going on? Oh my God, I can't lose her. Okay, that's how we open this. Oh, the hammer's right here. Oh, great. Go, go, go, go.  Go, yes. Okay, nice. We managed to dodge boots this time, and we grabbed the hammer. Okay, the key was... Okay, we need to find that door. Instead of the key was inside, I just need to know where the heck I was at, because this map is a little confusing, and now the duck is... the goose is bringing something out. Oh yes, that is a very nice portrait of yourself. No, okay, keep going, keep going. Okay, we have to go this way. I think it's somewhere... Oh, I have to go back in. Okay, there it is. Use the hammer on the planks. Yes. Okay, that was easy. Time to get out of here. Okay, we can't. Okay, we have to go around. Oh my gosh, this goose is going crazy. Okay, let's see what he has to say. Looking for trouble, and if not, I can find it. I will create it. Dude, I'm in a little bit of trouble myself right now, goose. Thank you so much for the offer, though. Oh, she comes. Okay, so we have the key. We just have to race to the gate and get the heck out of here. Hopefully this works. Please? Wait, that key doesn't fit? Are you kidding me, bro? I should have known Dora would scream with me. Dude, so now what? I gotta find the real gate key. What? That doesn't even make any sense. Okay, I guess it was a fake key. And now we gotta go find the real one. Okay, wait, is that a map? The map! That girl killed me. Now you're next, Swiper. Whoa, okay, I have no idea what just happened there. Okay, and we have to go through that door. We just have to lose Dora, though. Here it is, here it is.  Great, it's a door leading to another door. Okay, yes, what is that? You killed me. Ran me over and left me behind to bleed out in this. Dude, I have nothing to do with this. What? I am in... Oh, great, we need to get out of here. Okay, where the heck is the real key at? Somebody please goose tell me where the real key's at, bro. I know you know everything. Wait, what is that? Is that the key? Please let it be the key. Yes, goose, we found the key together. Even though I did all the work. Oh my God, Dora's gonna be right here. Go! Time to get out of here. Okay, now we have to run towards the gate. Bro, she is going faster. She's going faster. Oh, we're moving slower! Oh my God, what the... Okay, so I think that boot actually helps you. It seems like he pushed her back. Okay, follow the arrow, follow the arrow. Goose, now is not the time we're about to escape here, man. Come on, please let this be the actual key. And there's the gate. Okay, open sesame. Run, Swiper! Kill me, oh. Oh my, okay. All right, you guys, well, there we have it. Oh, goose is going after my cursor now. Oh, look, he's drifting. All right, ladies and gentlemen, check. Hey, I don't even know what I'm saying. All right, ladies and gentlemen, well, there we have it. Dora is dead. Oh, Dora is not dead. I played this game like four years ago when I barely started my channel. It was a long time ago, and I saw the remastered version. I was like, why not? Let's go pay the visit. Ruined childhood plus horror games? Seems like a good combination to me. Even though it was a pretty good game. I'm not going to lie. And shout out to Dave Microwave Games. He's the one that created this game. And he actually did create that SpongeBob around the clock. It was a pretty famous game that was going around on YouTube. Pretty awesome, man. Thanks to him and awesome games. Well, thank you all for watching. Thank you all for the amazing support. As always, truly appreciate it. And so does Goose. We will see you all in the next one. Bye.


Broadway's my beat from Time Square to Columbus Circle, the gaudiest, the most violent, the lonesomest mile in the world. Broadway's my beat with Larry Thor as Detective Danny Clover. In the first week of the new year, Broadway has beside itself with promises. The new leaves have been turned over, the resolutions made, the wife has been kissed in the morning. It's the time of only one martini before dinner, the high protein diet, and let the blonde stroll by without lifting your hat. Also it's the week of the clearance sales, good slightly handled and non-returnable, but at a bargain. So buy something, live it up, it's 1952, the year the boat will come in, it's got to be the year. In the corridor where I was, the new year was a thing that came and went, paced off with the quiet steps of nurses, the corridor of routine and pain, emergency hospital. Danny, you got here fast Danny. What's the trouble Dr. Sinski? Come on. Report that came with the man said his name was John Dobson. Can he talk? No. How bad is he? Well, I'm doing everything I can, in here. One thing, he's not in any pain. There's the report over on the table with his effects. John Dobson, Park Avenue address, found in Kamato's condition in a park car in East River Drive. Motor's still running, 8.20 p.m. 40 minutes ago Danny. What's the matter with him Doctor? Poison. Uh huh. Carrying a lot of money, over $300 in his wallet. I've got saliva samples down in the lab Danny. Until then I have to treat symptoms. You can't tell what kind of poison, you may be self-administered. I doubt it.  I'd say the man was driving when the poison hit him, pulled over to the side. That's your business. Pardon me Danny, I've got mine to do. The shadows gather, wait on the edge of the circle of light that is a yellowing barrier against them, holding from them the man, locking from them his life. The shadows wait for a night's decision to be made. The beggars of darkness eager for the handout of death, working quietly within the fortress of light, Dr. Sinski, aware of the hunger of shadows, moving quickly against them to deny them a man's dying. Watch it, then leave them alone with it. They own out of the Park Avenue address of John Dobson. Be told that his wife is at home, ascend to the 30th floor apartment. How clear does it have to be before it penetrates? There's no one home.  The only color, the pale thin lips like an old scar. Get out before I have you thrown out. I'm from the police Mrs. Dobson. I don't care who you are, you've no right to come here to wake me, to make me show myself this way. Your husband's in the police emergency hospital. He's been poisoned. Come in. You could have phoned, you know. That's true. We could have. And you wouldn't have seen me like this, in the way you're privileged. Few men have ever seen me in this... even John, he has his own bedroom. Maybe it didn't register, Mrs. Dobson. I said your husband has been poisoned. He's in the police emergency hospital. Of course I'll go to him. If that's what you're implying. If you'd only phoned, I could have worn a proper... Oh, now I just have to throw on the first thing that... how bad is it? He's dying.  Is that how it's done? It crushes you? I love him. That answer your foolish question? He was found in a parked car alone. You know where he was before that, Mrs. Dobson? With me. We had a candlelight dinner here in the apartment. Over a dessert he kissed me, full on the lips. Said he had to go out for the evening. It was hours ago. Did he tell you where he was going? He whispered it against my ear. To his old friend, Floyd Gilmore. John and he exchanged old school ties for Christmas. Where do I find him? Floyd? He has a devastating little flat in Gramercy Park. Done in bachelor's souvenirs. The longer you keep me, the longer it'll take me to get to John's side. I'll drive you down, Mrs. Dobson. I want to be lovely for him. That'll take a while. So you won't bother waiting, will you? Of course you won't. Yes, what is it? Your name, Floyd Gilmore? I'm Danny Clover, police. You might have come in. Well, what for? It's about John Dobson, I understand. What about John? Something's happened to him. He might die. Yeah, you better come in. In here. He might die? He's been poisoned. He was found a while ago in his car. John? I just talked to his wife. She said he'd been with you. Uh, John never got here. Well, it's a matter, don't you believe me? What was he coming to see you about? I asked you something, don't you believe me? I told you John never got here. I told you something, too. He was coming over to see me, that's all. What for? To borrow a book? Play chess? What? You can take fingerprints, mister. I'm telling you, John wasn't here. That's going to be pretty tough to prove, Mr. Gilmore. John Dobson had plenty of time to be here, be poisoned, and leave. Be poisoned? You mean be murdered? If John Dobson dies, it'll be murder. I'll tell you why he came here. Came here? You said he didn't. All right, so I got mixed up. I got a quirk. I get my conjugations mixed when I'm under mental stress.  Do what you want, mister.  I had a friend I wanted John to meet. Mind if I ask why? John doesn't get along with his wife. She didn't approve of his outside interest. You were going to introduce him to an outside interest? Well, this girl is this friend of mine. He's a nice kid. Same kind of personality as John. Oh? That's right. Pretty? Sure. John was, well, fetching's the word. Not as pretty as Edna. Not nearly as pretty as John's wife. What? You could never understand that about John. A beautiful wife like Edna, all her dough. Why, he had so many outside interests. Why, you should... Where do I find this friend of yours? Elizabeth? At the new Howard Hotel. Ask for Isabelle Martin, mister. Oh, and tell her I'm sorry. Tell her we couldn't make it tonight. The new Howard Hotel. A discreet brownstone in the discreet east sixties, designed to recall the foamy days of Victorian elegance. The reproductions of antique hitching posts, standing in frozen wonder at the sleek and snarling eight-cylinder beasts flotting their chrome. And the lobby hung with maroon velvet, its frayed tassels swaying gently over simulated marble, and presiding over it a frocked man savoring a well-thumbed pocket edition of Charles Dickens. Take courage by the hand, break through the mists of old lavender, dare to ask him for Isabelle Martin. The consequence is no more than a compassionate smile, a whispered room number, and a ride in a self-service elevator hung with the framed messages of beauty salons and credit dentistry. The elevator finally ascends to the heights of the fifth floor. Footsteps in the hall. I open my door and let out a call. Hi, John. Not John. I'm from the police, Miss Martin. Police? Floyd said he'd send me John. He sends me you. Good old Floyd. Well, good old Floyd. I want to scratch his face. Let's go inside, Miss Martin. That's a lovely idea. Lovelyest idea of the century. Let's everybody go inside. Let's everybody have a drink. Yes. Take a sip of mine. I was saving it for John, baby. He won't be here. All right for him. You take a sip of mine, baby. You think you can understand what I'm going to tell you, Miss Martin? The things this girl understands. I'm not as gone as all that, mister. Lonesome little drinky while waiting clears the brain. So tell me. John Dobson is dying. He was poisoned. That's why he stood me up, huh? Because he's dying. You waited for him. He never showed up, is that it? That's it. Do you mind if I look around? Love it. Love it. Note the tasteful arrangement. There's another glass here on the night table. Part of a drink in it. That's where it's been hiding. Tell me a lonesome little drinky. I put you down and forgot all about you, didn't I? I poured myself a new one all the time. Lonesome little baby. Pardon me, Dinky. Phone's ringing. Hi, then. Hello. This was Isabelle. For you, mister. Danny Clover speaking. Dr. Sinski, Danny. Get down here. There's nothing more I can do for him. Right away, doctor. Get me an empty bottle, Miss Martin. I want to take your forgotten drink with me. Empty?  Take your pick. Dr. Sinski, how is he, doctor? Not a chance. Mrs. Dobson, Danny. She's in there with him. It's such a time. You better leave them alone. Did he talk? Say anything? Once. For a second, Danny opened his eyes and said his wife's name. Said Edna. Said my beautiful wife, Edna. Beautiful? Even in all her grief, I caught myself staring at her, watching her. Look. Look at her. Even in all her grief. The circle of shadows was around them. Around a man and his wife. The man with pale death at his cheek. The woman luminous. The face touched with infinite sadness of infinite loveliness. The tear at her eye's edge not falling, but held there. The small glistening of despair. Johnny. Johnny. John. Dear. Johnny. He's dead. It's my beat written by Morton Fein and David Friedkin, and starring Larry Thor as detective, Danny Clover. Two of our CBS Radio gals are at opposite extremes intellectually. Marie Wilson is empty-headed, my friend Irma. And Eve Arden is English teaching, our Miss Brooks. But in spite of this difference, Irma Peterson and Connie Brooks have two things in common. They're both funny, and they're both yours to laugh at of these same CBS radio stations Sunday evenings. Enjoy them both tomorrow night. Not only so many of its night times, Broadway has already used them, drained them of their neon, their glitter, their anguish. Broadway takes its place in line to wait for the new fallings of darkness as it did on the fading edge of this nighttime that had come like other Broadway nights. It sparked a spectacular as in a winking light. It opened corridors for solitude to walk. It carried on its wind laughter and shock. And Broadway stands dazed and still waiting for this night to end. Where I was the night wouldn't depart because it must linger on the face of a woman on its beauty, on the tear that held the grief for her dead husband. It must listen close because her weeping is gentle, distant. Mrs. Dobson. Mrs. Dobson, you... Don't look at me. Don't dare look at me. I'll take you home. There's no need. I'll manage. If you want to lie down and need something, the matron... You have a dressing room? What? A room. Something with a mirror in it. A brightly lit mirror. I suppose there's one somewhere in... I shock you, Mr. Clover. I shock you because I insist on being beautiful even while Johnny lies dead. Is that something awful for a woman to want? To be beautiful for her dead husband? I don't know. You know it now, Mr. Clover.  The lovely one is the woman Johnny knew. The woman Johnny saw when he died. There was never any other. You understand that, Mr. Clover? I think so. Good. Now leave me alone with him, will you please? I mean alone. No gratuitous sympathizers. No one to see me with tears on my face. Alone. To you, Danny, a good, good morning. You slumbered well in the land and nod, I hope. Oh, that's a good, you know. I didn't get home from the hospital until late. When I finally got to bed... Well, here's something that'll revive an otherwise drab day, Danny. Surprise. Electric fan? What for? Startles you, huh? The self-same fan you commissioned me to have repaired last July. I saved the department money. All fixed and ready to go. To Witt. Like Miami. This is the same... The same fan by which we have called other names. Bout a corn a pot to the quick and revived by me, Geno Tartaglia, plus the proto-tools Mrs. T slipped into my galoshes for Christmas. Professional, huh? Feel the breeze. It's January, Geno, turn it off. Geno? Yeah. Any other puttering you'd like to have done around here? Just... What are the word about the medical examiner's report? Roger. John Dobson did indeed die from a poison which Dr. Sinski did label as being of the alkaloid family. Specific poison and time taken will not be known until autopsy is performed on the vital organs. What else have you got? Some background material on Mr. and Mrs. John Dobson dug out by obediently yours and the good detective Muggevin. If you please. Indeed. Mr. Dobson lived by no visible means of support. Nice house. Nice clothes. No job. Prior to his exchanging marriage vows with Mrs. Dobson, he lived off handouts from friends. Go on. Mr. Dobson did attach himself and married Mrs. Dobson while she was still in with those weeks. Oh? Hadn't Dobson was married before? To a Timothy French deceased. What did Mr. French die of, Geno? Could you find that out? I did. I did. From an accident. Mr. French was a wheelchair case from his youth. Three years after his marriage to his wife, he had a misfortune, fell out of his chair down the steps. And Mrs. Dobson inherited it as a state, isn't it? Wait a minute, Danny. I'll look in these reports just a second. Never mind, Geno. Put them on my desk. You did real fine today. Just wait till July when you can enjoy that fan, Danny. The nice things you'll say about me. And study the reports the sergeant leaves on your desk. Find that the widow of Timothy French had inherited $250,000, more than half of it in insurance. Find the name of the insurance broker who had handled it. Jonathan Harvey, 12 Broad Street. Go to him. Talk to him. Let me make my puny attempt at trying to understand you, Mr. Clover. Go right ahead. I'll have to block it out on this scratch pad. Now, let's see. Under a general heading, we have your reinvestigation of the death of Timothy French and his first husband. That's right. Then draw a line and underneath your reasons for doing so. What shall we put down, Mr. Clover? Mrs. Darbson's second husband died last night of alkaloid poisoning. Newspapers added at great length. I read the head, ah-ha! I see what you're after, Mr. Clover. Thank you. Now I can fill in this side. Here, we have death of husband number one. Here, death of number two in the short space of two years. Hmm. Interesting. I'm glad you agree. However, I'm afraid that's as far as it goes, Mr. Clover. Oh, tell me why. Perhaps you don't know that my company conducted a most thorough rundown on Mr. French's death. Found it accidental. Though I am an insurance man, Mr. Clover, I am also a friend. Huh? Friend, a confidant to all my clients. As I was to Tim French. As I would be to you. You knew him well? My dear young man, I nurtured his romance with Edna. How did you do that? Edna was a teller at the Ruxton Bank on Wall. One day, I wheeled him along with me. Well, I made a deposit for him. And that's where he met Edna Dobson in the bank. She was plain then. Thoughtless fellow could call her ugly. And Tim was a, forgive the word, a cripple. Unwanted people. They meet sometimes, fall in love and get married. Then one of them dies in a fall.  It's useless, Mr. Clover. We spent thousands of dollars proving it to ourselves. Tim died accidentally. So leave there and decide a thing. Mrs. Edna Dobson, ex-bank clerk, widowed twice, was a woman you wanted to talk to again. Go to her apartment house. She's not the home you're told by a maid who opened the door for you and got right down on her knees again to dust. Where is she?  Which one? Lawson's naturally.  You a husband? No, I'm afraid not. I want to see you. Oh, my friend, eh? Who we got under the dryer belongs to you. I want to see Mrs. Dobson. What have you been doing all morning, man? Mrs. Dobson's been here since nine. Facials, hair set, contouring, refinishing, re-weaving, everything on the menu, and you walk in just as she walks out. I don't envy you. Oh, why?  Frankly, you don't look as if you can afford it. I'd get fired if Mind Here Lawson knew I was talking like this. Mind Here is Dutch, you know. No, I didn't. But I like your face to be blunt.  The dough that Edna Dobson spends on lotions and contours and facials since the first day she came in here. When was that? I remember because when she stepped in here, Mind Here said, I accept the challenge. Her first husband's funeral was at noon. Her appointment was at four. And since then she spent a lot of money on it. Not only with us. Take a walk down the street to Rexford's. Find out the dough she spends there on clothes to make her look of the form divine. But believe me, save yourself the walk. I know. Well, I want to thank you for all you've done for me. Not that I dislike Mrs. Dobson, you understand. Just that I like to be frank. Understand what I mean? Oh, Mrs. Dobson, come in. Sit down. Sit down. Here? This is police headquarters, Mrs. Dobson. Tax payers don't furnish this with upholstered furniture. It's so dusty. Oh, Detective Margaret. Uh-huh. Now you can sit down, Mrs. Dobson. Thank you. And I want to thank you for coming down here to see me. Did I have a choice? Well, I didn't want to barge in on you again.  Thank you again. Very considerate. Uh, I was telling Mrs. Dobson out in the hall how nice I thought she looked after all she's been through. He's right, Mrs. Dobson. You do look very lovely. Thank you. Why did you ask me to come here? Well, I have a few things I want to talk to you about. I see. We were surprised to hear you'd been married once before, Mrs. Dobson. What of it? I think it's important that we should know about your first husband. No, what about him? How he died. He died four years ago. He fell down the steps in his wheelchair. Did you push him? I'm sure there's nothing else you want to say to me. Did you push him, Mrs. Dobson? For your information, the insurance adjusters asked me the same thing. If they hadn't reached the conclusion that it was an accident, would I be here? Sit down, Mrs. Dobson. Close the door and sit down. This will only take a few moments. Thank you. Why did your Mr. Muggevin ask me that question? Well, you don't have to ask him, Mrs. Dobson. Ask me. I'll tell you why. Because his death left you a rich woman. Then by your reasoning, every woman who inherits money is a murderer. You met your first husband while you were a teller in a bank, didn't you? How did you meet your second husband, Mrs. John Dobson? Shall I tell you? If you don't mind, Mrs. Dobson. I was eating salted peanuts in a bar. He sent over a note and a bottle of wine. Who paid for the wine? What? Lieutenant asked you who paid for the wine. Who do you think paid for it? I doubt whether Mr. Dobson did. He was pretty broke from what I could find out. That's right. He was broke. I love it. I fell in love with him. Not right away, but eventually I fell in love with him. Mr. Dobson was a good-looking man. I imagine a lot of women fell in love with him. But I married him. When did you find out he was running around with other women, Mrs. Dobson? He's dead. Leave him alone. Lieutenant asked you, Mrs. Dobson, when did you find out about his wife? Leave him alone. Leave him alone. Did he start taking interest in other women when he barged in on you one day like I did and saw you like I did? What difference does it make? Here's the way we figure, Mrs. Dobson. I know what you think.  I don't think we'll ever know about your first husband unless you want to tell us. It was an accident. Here's the way we figure, Mrs. Dobson. Your first husband died and you came into all that money. With money, you can make yourself beautiful. Beauty salons, custom dresses, the works. The way you always wanted to be. Isn't that right, Lieutenant? Then you met a handsome man, a man who believed you were beautiful, John Dobson. He married you. He had no job. He lived off you. You were satisfied with that as long as he believed you were lovely. She is lovely. I don't care what you say. Then he changed. He started to go around with other women. You couldn't tolerate that. You poisoned him. You ever see a woman who could wear clothes like her? No. No, I haven't. The way she does her hair, yeah. Beautiful. You think so? The reporters will think so, too. The photographers, too. The pictures of you in all the papers. All your exclusive clothes. Every woman in the city will be jealous. Just when women look at me, I can tell what they're thinking. They are jealous. They'll be interviewed and understand. All the men, the women. The women crowding the courtroom to get one peek at you. I killed them. I killed both of them. Will the reporters be here soon? Broadway's sleeping now. The furious avenue of the night is still.  Without beginning, without end. The dumping ground of refuse and ashes and leftovers. The neon words have turned off. But look there. Where the sidewalk meets the street. It's your name. Written on water. It's Broadway. The gaudiest. The most violent. The lonesomeest mile in the world. Broadway. My Beat. Tomorrow night, the gal who made good Tuesday nights, Audrey Totter as Millie joins the Sunday lineup on most of these same stations. Yes, from now on, you can meet Millie and all her hilarious friends, too. Sunday nights on CBS Radio. On the more serious side, tomorrow marks the debut of The People Act, CBS Radio's new series about community problems solved by American communities. You'll find out more about it. You'll find The People Act a fascinating, rewarding experience every Sunday night on CBS Radio, starting tomorrow night. Phil Anders speaking, and remember, those lovable rascals Amos and Andy are here every Sunday on the CBS Radio Network.


Okay, so this one's a little different. We do have to remember what we had talked about earlier today about the strong acids, okay? So it says what is the pH of 1.0 times 10 to the negative fourth molar HCl solution, okay? So we know what the concentration of HCl, that the formula H3O plus concentration, right? Or the H plus concentration, whichever one you want to do. Let's just do H plus, please, okay? Do we have that number? Are they H plus concentration? Is that given to us in the equation? Uh-uh, so we've got to remember something. We've got to remember what happens to HCl when it's put into water, okay? What happens to it? It's a strong acid, so it does what? Completely dissociates, okay? Very good, that's very good, do you remember? So let's do the reaction equation. And again, H plus, H3O plus same thing, right? HCl, do the easy one, right? So breaks up into H plus plus Cl minus, like that, okay? And it's a straight arrow because it's a strong acid that completely dissociates. So if you wanted to, I can see some of you really wanted to, concentration of this, so if you remember from, what was it, chapter 8, right? When we're doing the mole going in the reaction equation, moles of one reactant to find the moles of the product, right? So we know the number of moles of this, right? The molarity of this. So we should know the molarity of these two, right? What's the ratio from this to this to this? One to one to one, right? So the concentration of this should be the same concentration as this and the same concentration as this, okay? So if we know this concentration, we also know that H plus concentration, we also know the Cl minus concentration for that matter, not that it's going to help us in this reaction, but are this problem. But we do know that, we need to get in because it'll confuse you. Again, try real hard with those sig figs, okay? It's not always the easiest thing to remember, especially for you guys. Notice, no units. Is this acidic, basic, what? Acidic, right? Why? Below four. Oh, below seven, sorry, it's not below four. Below seven, so, so.