Uploaded February 2013 | Updated September 2026, 1 hour ago
An introduction to t tests for one population mean. I briefly discuss when we use the test, and when we would use a z test instead. I also briefly discuss the hypotheses of the test, and the p-value for different alternatives. I then work through an example. (If you are comfortable with the basics of hypothesis testing, and understand the difference between t and z procedures from confidence intervals, then much of this video may be review.) If you are just looking for an example, it starts at 7:00.
The reaction time data is simulated data with the same summary statistics as found in:
Armstrong et al. (2012). Mild Dehydration Affects Mood in Healthy
Young Women. Journal of Nutrition, 142: 382-388.
An introduction to t tests for one population mean. I briefly discuss when we use the test, and when we would use a z test instead. I also briefly discuss the hypotheses of the test, and the p-value for different alternatives. I then work through an example. (If you are comfortable with the basics of hypothesis testing, and understand the difference between t and z procedures from confidence intervals, then much of this video may be review.) If you are just looking for an example, it starts at 7:00.
The reaction time data is simulated data with the same summary statistics as found in:
Armstrong et al. (2012). Mild Dehydration Affects Mood in Healthy
Young Women. Journal of Nutrition, 142: 382-388.








![Introduction to the t Distribution (non-technical)
A brief non-technical introduction to the t distribution, how it relates to the standard normal distribution, and how it is used in inference for the mean.
For those that use R, below are the R codes to find the values found in the video.
z value for a 95% interval:
qnorm(.975)
[1] 1.959964
t value for a 95% interval (5 DF)
qt(.975,5)
[1] 2.570582
t value for a 95% interval (10 DF)
qt(.975,10)
[1] 2.228139 Introduction to the t Distribution (non-technical)](https://i.ytimg.com/vi/Uv6nGIgZMVw/mqdefault.jpg)

