Analysis of variance (ANOVA) is a statistical method used to compare the means of two or more groups. It is a parametric test, meaning it makes certain assumptions about the data, such as that it is usually distributed and the groups groups are equal (Kim, 2014).
One-way vs. two-way analysis:
According to (Connelly, 2021), a one-way ANOVA is a statistical test used to compare the means of three or more groups. On the other hand, a two-way ANOVA is a statistical test used to compare the means of two or more groups. The main difference between a one-way ANOVA and a two-way ANOVA is the number of independent variables. A one-way ANOVA has one independent variable, while a two-way ANOVA has two. The null hypothesis for ANOVA is that there is no difference between the means of the groups. The alternative hypothesis is that there is at least one difference between the means of the groups (Yigit & Mendes, 2018).
Application to my research project:
According to (Olaya, Ovalle-Muños & Urbano-León, 2020). In my research project on construction pollution, I can use the following two methods:
One-way ANOVA
- To compare the levels of air pollution in different neighborhoods near construction sites.
- To compare the levels of noise pollution in different neighborhoods near construction sites.
- Tt to compare water pollution levels in different rivers near construction sites.
Two-way ANOVA
- The aim is to compare the levels of air pollution in different neighborhoods near construction sites while also considering the type of construction taking place.
- The aim is to compare the levels of noise pollution in different neighborhoods near construction sites while also considering the time of day when the construction takes place.
- The aim is to compare the water pollution levels in different rivers near construction sites while also considering the river divers from the site.
Post- Hoc analysis with ANOVA:
A post-hoc analysis is a statistical test conducted after an ANOVA to determine which groups are significantly different from each other. Post-hoc analyses are typically used when the ANOVA results are significant, meaning that there is at least one difference between the means of the groups. Post-hoc analyses can be a valuable tool for researchers, as they can help identify which groups are significantly different. However, it is essential to remember that post-hoc analyses are unnecessary and can increase the risk of Type I errors (Kucuk, Eyuboglu, Kucuk & Degirmencioglu, 2016).
Conclusion
In my research project about construction pollution, I might use a one-way ANOVA if I'm only interested in comparing pollution levels in different groups. For example, I might use a one-way ANOVA to compare the levels of air pollution in different neighborhoods near construction sites. However, if I'm interinterestedomparing the pollution levels in various groups while also considering the effects of another factor, I could use a two-way ANOVA. For example, I can use a two-way ANOVA to compare the levels of air pollution in different neighborhoods near construction sites while also considering the type of construction that is taking place.
References
Connelly, L. M. (2021). Introduction to analysis of variance (ANOVA). Medsurg Nursing, 30(3), 218-158.
Kim, H. Y. (2014). Analysis of variance (ANOVA) comparing means of more than two groups. Restorative dentistry &
endodontics, 39(1), 74-77.
Kucuk, U., Eyuboglu, M., Kucuk, H. O., & Degirmencioglu, G. (2016). It is essential to use proper post hoc tests with ANOVA. International journal of cardiology, 209, 346.
Olaya, J., Ovalle-Muños, D. P., & Urbano-León, C. L. (2020). Functional analysis of variance of air pollution caused by fine
particles. Universitas Scientiarum, 25(1), 1-16.
Yigit, S., & Mendes, M. (2018). Which Effect Size Measure is Appropriate for One-Way and Two-Way ANOVA Models?: A
Monte Carlo Simulation Study. Revstat-Statistical Journal, 16(3), 295-313.