What Factorial anova is
Factorial ANOVA is a statistical technique used to analyze the effects of two or more independent variables on a single dependent variable. It can be used when there are multiple factors that influence the outcome of an experiment. The goal of Factorial ANOVA is to determine which factors, if any, are significantly related to the dependent variable.
Steps for Factorial ANOVA:
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Formulate the research question: The researcher must first formulate the research question they wish to investigate. This includes identifying the independent and dependent variables of the experiment.
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Set up the experimental design: The researcher must decide on the number of factors and levels to be included in the experiment.
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Collect the data: The researcher must collect data from the experiment that is in numerical form.
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Calculate the sum of squares: The researcher must calculate the sum of squares for each factor and the total sum of squares.
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Perform the ANOVA calculations: The researcher must then calculate the F-test statistic and the p-value for the overall model.
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Interpret the results: The researcher must then interpret the results of the ANOVA to determine if the factors have a significant effect on the dependent variable.
Examples
- A study of whether the average reading comprehension of students differs between three different curricula.
- An experiment to determine the effect of temperature on the growth of bacteria.
- An examination of the effects of multiple predictors on student math scores.
- An analysis of the effect of gender and age on political attitudes.
- An investigation of the impact of different teaching methods on test performance.