Two way ANOVA
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The document discusses analysis of variance (ANOVA), which partitions total sum of squares into components due to factors and error. There are two types of ANOVA: one-way and two-way. Two-way ANOVA compares mean differences between groups split across two independent variables and determines if there is an interaction between the variables on the dependent variable. An example tests if gender and education level interact to influence text anxiety.
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Two way ANOVA
- 2. The ANOVA investigates independent measurements from several treatments or levels of one or more than one factors. The techniques of ANOVA consists of partioning the total sum of squares into component sum of squares due to different factors and the error. It is basically of two types : ONE WAY ANOVA TWO WAY ANOVA
- 3. The two way ANOVA compares the mean differences between groups that mean differences between groups that have been split into one two independent variables. The primary purpose of a two way ANOVA is to understand if there is an interaction between the two independent variables on the dependent variables. Example : We could use a two way ANOVA two understand whether there is an interaction between gender and educational level on test, are your independent variables, and text anxiety is your dependent variables.
- 4. The two or more categories, independent group are founded. The dependent variables should be measured the continuous level. There should be no significant outliers. There needs to be homogeneity of variance of each combination of the groups of the two independent variables.
- 5. HO1 = all the groups have equal stress on the average. HO2 = Both the gender groups have equal stress on average. HO3 = The two factors are independent or that interaction effect is not present.