I'm glad it helped! I made this video because the textbook I use lacks the details needed to construct these intervals. Apparently this is a common flaw in stats texts. Good luck with your studies :)

Glad this was helpful!

Thanks so much and I am glad that it was helpful!

Great question. Poisson Distributions are not based on a sample size (n) whereas one of the requirements of the Binomial is that we have n independent Trials. Also, the Poisson looks for occurrences that occur over an interval - time, distance, length, days, hours etc. Finally, in a Poisson Distribution, instead of having P (probability of success) we are given the Mean (or Lambda) and that average remains fixed across all observations. I hope this helps!

@@lsw278 thank you

I'm glad this helped.

Thanks for the question. In Permutations, always use the number from which to choose as the n. In your case, this would be 12 if you have 12 games to be played. Then for the r, think of that as how many are "required" meaning how many are you looking for. This would give you 12Pr. I hope this helps.

I'm glad you found this helpful!

I'm glad that this was helpful!

I'm glad that it helped!

That's the whole reason I made this video - finding a way to do this WITHOUT R! Glad this helped

Great question! (Sorry for the long answer, but it's an important component of this approach to regression). In logistic regression, the natural log function is used in the likelihood because of its properties that make it well-suited for modeling probabilities. The logit function, which is the natural log of the odds ratio, converts the probability of success to a linear function of the predictors. It also converts the probability of success to a linear function of the predictors. This linear relationship between the log odds and the predictors is convenient for modeling with linear regression techniques.

I'm glad it helped. Using Excel for this is a little clunky, but it gets the job done! Good luck with your studies

I'm glad this helped!

I'm glad to know that I'm still helping all these years later.

THANKS! This is a great time saver and appreciate the hint.

I'm so glad it helped!

Do you have your calculator set to BGN? I am also set at 5 decimal places. Try that and hopefully it will work.

Valid point. The Standard Error of the Mean (SEM) is used when constructing a Confidence Interval (CI) for the Population Mean because it provides an estimate of the variability or precision of the sample mean as an estimator of the population mean. When we take a sample from a population to estimate the population mean, there is inherent variability due to random sampling. So, when constructing a Confidence Interval for the Population Mean, we use the SEM to determine the margin of error around the sample mean. The larger the sample size, the smaller the SEM, At a n=36, we meet the large sample size requirement of the CLT (n=> 30), but if we want our CI to be more precise, we would take a larger sample, if possible. I hope this helps.

I'm glad that it helped!

You are using a cumulative table that shows the total area to the left or right of a point on the curve. So, the table is saying that 97.50% of the data falls to the left of a Z Score of 1.96. This leaves 1-.9750 = 0.025 or 2.5% of the data to the right of that Z Score. If you have a 2 tailed test at alpha = .05, then that .05 is divided by 2. This means that +1.96 and -1.96 are the Z Critical Values for a two-tailed test at alpha = .05.

Because given normal distribution, 50% of the data falls to the right of the mean (center of the distribution) and 50% falls to the left.

I'm glad that it helped!

Glad that it helped!

This is NOT a sampling distribution. The Poisson Distribution is a discrete variable probability distribution. Although Lambda (Mean) is derived from a sample, the value of Lambda then applies to all occurrences of the event. So, if we know that Lambda is = 4 customers per hours, then it will remain 4 per hour for an infinite number of trials. This will remain true until something significantly changes in the population and we establish a new value of Lambda. I hope this helps.

@@lsw278 thank you very much. It's clear now

RFR is the "Risk Free Rate" and "RP" is the Risk Premium

Awesome! So glad it helped.

Glad it helped!