Would someone (CPK I’m looking in your direction) deconstruct the ANOVA table for us? I was looking at that over the weekend thinking that my dog is going to understand the concept sooner than I am. I would be very grateful if someone could do this for me.

Isn’t it just the F-Distribution table? Or am i crazy?

Analysis of variance (ANOVA) is a statistical procedure for analyzing the total variability of a data set. Output of an ANOVA table consists of: Total sum of squares (SST) measures the total variation in the dependent variable. Regression sum of squares (RSS) measures the variation in the dependent variable explained by the independent variable. Sum of squared errors(SSE) measures the unexplained variation in the dependent variable. Thus, total variation = explained variation + unexplained variation, or SST = RSS + SSE

have sent you an email… explaining the problem 7 check it out.

ohhhh i gotcha, you were talking about the output of the ANOVA … i thought you were asking about how the F-Distribution used in the analysis… my bad What is it that you’re not understanding? I just finished that section, so I have a decent understanding. (i say decent, but there’s a good chance your dog could still explain better haha)

ditchdigger2CFA Wrote: ------------------------------------------------------- > Analysis of variance (ANOVA) is a statistical > procedure for analyzing the total variability of a > data set. Output of an ANOVA table consists of: > > Total sum of squares (SST) measures the total > variation in the dependent variable. > Regression sum of squares (RSS) measures the > variation in the dependent variable explained by > the independent variable. > Sum of squared errors(SSE) measures the > unexplained variation in the dependent variable. > Thus, total variation = explained variation + > unexplained variation, or SST = RSS + SSE You basically answered your own question. The ANOVA table breaks down the total variation in the dependent variable into that part explained by the regression (RSS - the regression sum of squares), and that part that remains unexplained (SSE - sum of squared errors). In addition, you’ll also find the mean sum of squares, which is the total sum of squares divided by the degrees of freedom. so, MSSR = RSS/k and MSSE = SEE/(n-k-1). The total degrees of freedom is always n-1, so MSST = SST/(n-1). The F-stat calc is also provided as MSSR/MSSE, and should be compared to the F-dist with k degrees in the numerator and n-k-1 in the denominator. Finally, from the ANOVA table you can also calculate the R^2, which is the percentage of variation explained by the regression by R^2=RSS/SST.

cpk123 Wrote: ------------------------------------------------------- > have sent you an email… explaining the problem > 7 > check it out. Thanks, I got it. I’ll slowly go through it when I’m done working today.