One-Way Analysis    Targeting    Two-Way Analysis    Regression

In formal terms, ANOVA is a statistical technique that shows the contribution of categorical independent variables (e.g. roofing type) to the
variation in the mean of a continuous dependent variable (e.g. # months of food sufficiency). Observations of the independent categories,
such as different roof types, are classified separately and mean values are calculated for each category. These mean scores for each category
are tested to determine if there is a statistical difference between the mean outcome (e.g. months food sufficient) for each category
(good roof versus bad roof).

Tabulation (compare means function in SPSS) together with the ANOVA option is used to generate tables and test differences. In the example,
the mean values of months of food sufficiency by roofing type, and then by education level, are first estimated separately and then together.

Computing Steps for Two-way Analysis using the keast4j.sav dataset

Click analyze, select compare means, then means.

Select delivery, move to dependent list.

Select dbadro (bad roofing dichotomy) and move to independent list.

Click next (it should now read layer 2 of 2).

Select dlowedn, move to independent list.

Click options: cell statistics should have only mean and number of cases.

Click the box next to anova table and eta.

Click continue.