t-Test and ANOVA Testing- Classmate Response (2): Topic 5 DQ 1

t-Test and ANOVA Testing- Classmate Response (2): Topic 5 DQ 1


QUESTION-Compare the various types of ANOVA by discussing when each is most appropriate for use. Include specific examples to illustrate the appropriate use of each test and how interaction is assessed using ANOVA.


Classmate (Samantha) Response-


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). 



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







Analysis of Variance- ANOVA

Hello, thank you for giving me this opportunity to respond to your post. I gladly appreciate you taking your time to contribute to the Analysis of Variance’s discussion. I will only add a few points to your post, as your contributions are agreeable to the topic. Analysis of Variance testing is very crucial in analyzing clinical research, especially public health data. Therefore, a clear understanding of the concepts and types of analysis of variance is necessary for finding the study results of a sample. Hence, it is a statistical method that focuses on comparing two or more sample means.

In addition to the one-way analysis of variance, I would like to add that it is the easiest one to use (Sureiman & Mangera,2020).  The testing is done in two or more groups. These groups are normally categorically identified, thus making it easier to understand the association between independent and dependent variables in a particular sample. Based on the example provided in the post, the comparison between sprinter and smoking is observable and accurate. Therefore, the one-way approach can be used by researchers easily in articulating their work using several groups in a sample.

In the case of two-way analysis of variance, comparison can only be made between two categories of groups, thus too difficult for researchers to use (Sureiman & Mangera,2020).  For instance, checking if gender and educational level affect university students is a bit too complicated and broad study for comparison and decide on a concrete conclusion. This analysis of variance tends to find out if dependent and independent variables have any effect on each other and if both variables also affect the variance in the sample study.



Sureiman, O., & Mangera, C. M. (2020). Conceptual Framework on Conducting Two-Way Analysis of Variance. Journal of the Practice of Cardiovascular Sciences, 6(3), 207. https://www.j-pcs.org/article.asp?issn=2395-5414;year=2020;volume=6;issue=3;spage=207;epage=215;aulast=Sureiman





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