Analysis of Variance (ANOVA) is described as a hypothesis-testing technique that is mainly used in testing the quality of two or more populations by evaluating the variances of samples collected. ANOVA paves way in research to determine if the differences between two or more samples occur as a result of random error or whether they are due to systematic treatment effects that influence the mean in one group to differ with the mean in another (Sawyer, 2009).
ANOVA can be used to examine a workplace problem that affects employees’ performance. For instance, ANOVA will be used to examine whether the employees attitudes towards the organization’s policies and procedure affect their performance. Employees from different departments in the organization will be recruited and asked to report their perception towards the organization and how this affects their overall performance. 20 employees will be recruited for the experiment; whereby the control group will consist of 10 new employees who have not undergone organizational learning and training and the experimental group will be employees with at least 1 year experience working with the organization and have undergone organizational learning and training.
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The independent variable in this case is the employees’ attitudes towards the organizational policies and procedures – since it is the variable believed to have an effect on the employees’ performance. Additionally, there are two levels of independent variables; two groups of employees, one group with working experience with the organization the other without. The dependent variable is the employees’ performance. The null hypothesis is that there is no correlation between the employees’ attitudes towards the organizational policies and procedures with their job performance. On the other hand, the alternate hypothesis is that the employees’ attitudes towards the organizational policies and procedures have a significant impact on their performance. The alpha level would be Type I error; this is because the study would support the alternate hypothesis even though the null hypothesis may be true.
Reference
https://www.statisticshowto.datasciencecentral.com/probability-and-statistics/hypothesis-testing/anova/
Sawyer, S. (2009). Analysis of Variance: The Fundamental Concepts. The Journal of Manual & Manipulative Therapy ; volume 17, number 2. Retrieved from: https://pdfs.semanticscholar.org/33dd/9a33ed00d197b13dfa7eeb108023d2f1827d.pdf
