We are going to talk about ANOVA with independent samples in this lesson. First we will see why we need to introduce the ANOVA. An ANOVA is also called the analysis of variance and it could also be thought of as the omnibus hypothesis test. We are going to go over the notation in order to break down with the ANOVA details. And then we are really going to get into the partitioning or analyzing variance. Also, we are going to build up the F-statistics made up of those bits and pieces of variances and then finally talk about how that relates to the F distribution and hypothesis testing.
Lecture Slides are screen-captured images of important points in the lecture. Students can download and print out these lecture slide images to do practice problems as well as take notes while watching the lecture.
This book provides a clear and methodical approach to essential statistical procedures. It clearly explains the basic concepts and procedures of descriptive and inferential statistical analysis. This book features a new emphasis on expressions involving sums of squares and degrees of freedom as well as a stronger stress on the importance of variability.