Session: General Poster:

Student and researchers are often introduced to Analysis of Variance (ANOVA) Statistics by first studying one-way ANOVA examples. They then move on to factorial ANOVA statistics, for example two-way ANOVA, but often this is limited to balanced data. Balanced data are when the number of data values for each of the category (or group) is the same. When this is the case, the calculations are simple to do and the equations can easily be written to allow for each of the values needed to construct an ANOVA table. When unbalanced data are encountered, which is often the case in agricultural field studies, the data are often entered into a statistical program such as SAS to construct the ANOVA table. The most complicated situation is when data are completely missing in a two-way ANOVA design for some treatment combination(s). This can be handled by a SAS Type IV evaluation in the SAS GLM Procedure. In this presentation we will show how dynamic spreadsheets can be constructed to produce SAS Type IV sums of squares for two-way ANOVA tables using hypotheses testing. Different hypotheses can be constructed by the user.

K. Thomas Klasson Ph.D.

Research Leader, USDA-ARS

Appearances