A one-way ANOVA compares the means of two or more group means to see if these means are statistically different. This test is considered a parametric test. This type of testing is used to test the statistical difference between two or more groups, two or more interventions or two or change scores. An example of its use is to compare if there is a significant time difference between sprinter times based on their smoking status. Sprint time represents the dependent status while the smoking status represents the independent variable (One-way Anova, 2021).
A two-way ANOVA test seeks to evaluate if the independent variables have any affect on the dependent variable. It compares the mean differences for groups that have been split on two independent factors. An example of such comparison could be whether gender and educational level have any effect on testing anxiety of university students. Gender and educational level are the independent variables while test anxiety is the dependent variable (Two-way ANOVA, 2018).
References:
One-way ANOVA. (2021 October). Kent State University. Retrieved from https://libguides.library.kent.edu/spss/onewayanova
Two-way ANOVA in SPSS Statistics. (2018). Lund Research, Ltd. Retrieved from https://statistics.laerd.com/spss-tutorials/two-way-anova-using-spss-statistics.php
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