Uploaded May 2014 | Updated September 2026, 2 hours ago
A discussion of the sampling distribution of the sample proportion. I discuss how the distribution of the sample proportion is related to the binomial distribution, discuss its mean and variance, and illustrate that the sample proportion is approximately normally distributed for large sample sizes.
A discussion of the sampling distribution of the sample proportion. I discuss how the distribution of the sample proportion is related to the binomial distribution, discuss its mean and variance, and illustrate that the sample proportion is approximately normally distributed for large sample sizes.




![Finding the Appropriate z Value for the Confidence Interval Formula (Using a Table)
I show how to find the appropriate z value (using the standard normal table) when calculating a confidence interval. The version of the table used in this video gives the area to the left of the z value (and not the area between 0 and z).
For those that use R, below is the R code to find the values (see the video for illustrations).
z value for a 95% interval:
qnorm(.975)
[1] 1.959964
z value for a 75% interval:
qnorm(.875)
[1] 1.150349 Finding the Appropriate z Value for the Confidence Interval Formula (Using a Table)](https://i.ytimg.com/vi/grodoLzThy4/mqdefault.jpg)





![Introduction to the Continuous Uniform Distribution
A brief introduction to the (continuous) uniform distribution. I discuss its pdf, median, mean, and variance. I also work through an example of finding a probability and a percentile. I dont do any integration in this video.
For those using R, here is the R code to find the probabilities for the examples in this video:
P(X greater than 230) where X is U(200,250):
1-punif(230,200,250)
[1] 0.4
(punif yields the area to the *left*, and here we need the area to the *right*)
20th percentile of a U(200,250) distribution:
qunif(.2,200,250)
[1] 210 Introduction to the Continuous Uniform Distribution](https://i.ytimg.com/vi/izE1dXrH5JA/mqdefault.jpg)