Suppose we have some measurements of a quantitative variable and we calculate the average of these measurements. We can compare our average to a previously established mean or to the value that a scientific model says that the mean should be, that is to the theoretical world mean. It’s unlikely that the average calculated from our data is exactly equal to the theoretical world mean, but can we attribute the difference to just chance? Or is there evidence that something else is going on? This video covers how to carry out a statistical test when we are interested in the mean of a quantitative variable.
Download a SCORM package of the video with embedded quiz questions to deploy in a Learning Management System.
[This download requires a login. Name and password are available through this link.]
Stream the video without the embedded quiz questions by clicking on the video link below. Closed captions are available.
Notes on the video: Hypothesis Testing for Means
A point to consider for this video:
In this video, the P-values are often given as fractions. These P-values were calculated to many decimal places using statistical software, and then converted to an approximate fraction to emphasize how small they are.