Using statistics for testing variables within a dissertation has become popular among research scholars across the globe. You might find it quite difficult to choose from a wide range of statistical tests that can be performed for dissertations/theses written on different subjects. In this blog of mine, I would be discussing about ANOVA test that has emerged as one of the most popularly used statistical tests among doctoral candidates residing in different corners of the globe.
ANOVA is an abbreviation for Analysis of Variance. This is a statistical test that solely looks for significant differences between means. There are mainly four types of ANOVA models as explained below:-
In addition to the above 4 models of ANOVA, there are certain assumptions that exist while a doctoral candidate performs testing using ANOVA. Here is the list of these important assumptions:-
Fortunately, all the currently-available versions of ANOVA follow the above explained principles. So, what keeps you waiting? Now that you are well aware about ANOVA test, go ahead and simply opt for this statistical testing approach to ensure the effective testing of variables within the data collected as part of the research process. All the very best for your next statistical testing ventures!!!
- One-way between groups ANOVA- This model is used to test the difference between two or more groups. Under such testing regime, only one grouping is being used to define the different groups within an entire chunk of data.
- One-way repeated measures ANOVA- This model is used under situations where the individual has a single group on which he/she has measured something for more than once.
- Two-way between groups ANOVA- This model is used to look at complex groupings within a huge chunk of data and facts.
- Two-way repeated measures ANOVA- This model uses the repeated measured structure but also includes an interaction effect.
In addition to the above 4 models of ANOVA, there are certain assumptions that exist while a doctoral candidate performs testing using ANOVA. Here is the list of these important assumptions:-
- The expected values of the errors are zero.
- The variances of all errors are equal to each other
- The errors are normally distributed
- The errors are independent from one another.
Fortunately, all the currently-available versions of ANOVA follow the above explained principles. So, what keeps you waiting? Now that you are well aware about ANOVA test, go ahead and simply opt for this statistical testing approach to ensure the effective testing of variables within the data collected as part of the research process. All the very best for your next statistical testing ventures!!!
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