Uploaded May 2012 | Updated September 2026, 2 hours ago
I discuss the sampling distribution of the difference in sample proportions, and the formulas for confidence intervals and hypothesis tests for the difference in population proportions, based on the normal approximation.
This video does not do an example of the calculations (those are carried out in the video: Inference for Two Proportions: An Example).
The birth weight data is found in:
Shiono et al (1991). The impact of cocaine and marijuana use on low birth
weight and preterm birth: A multicenter study. American Journal of Obstetrics and Gynecology, 172:19--27.
I discuss the sampling distribution of the difference in sample proportions, and the formulas for confidence intervals and hypothesis tests for the difference in population proportions, based on the normal approximation.
This video does not do an example of the calculations (those are carried out in the video: Inference for Two Proportions: An Example).
The birth weight data is found in:
Shiono et al (1991). The impact of cocaine and marijuana use on low birth
weight and preterm birth: A multicenter study. American Journal of Obstetrics and Gynecology, 172:19--27.



![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)
![An Introduction to the Poisson Distribution
An introduction to the Poisson distribution. I discuss the conditions required for a random variable to have a Poisson distribution. work through a simple calculation example, and briefly discuss the relationship between the binomial distribution and the Poisson distributions.
Plutonium-239 example (an average of 2.3 radioactive decays per second).
Finding the probability of exactly 3 radioactive decays in a 2 second period:
dpois(3,2*2.3)
[1] 0.1630676
Finding the probability of no more than 3 radioactive decays in a 2 second period:
dpois(0,2*2.3)+dpois(1,2*2.3)+dpois(2,2*2.3)+dpois(3,2*2.3)
[1] 0.3257063
or
ppois(3,2*2.3)
[1] 0.3257063 An Introduction to the Poisson Distribution](https://i.ytimg.com/vi/jmqZG6roVqU/mqdefault.jpg)





