Analysis of variance
One-way analysis of variance (ANOVA) is a statistical approach that is generally employed when there is a need to compare data that have been collected from at least two samples (Freedman et al., 2007). It should be understood that one-way ANOVA may only be applied to numerical information because the data will be subjected to calculations for means and various other estimations. The ANOVA assay investigates the null hypothesis wherein at least two groups have been derived from a single population. In this setting, the research study can be envisioned to have resulted from at least two results and thus the variation in the responses of these groups need to be statistically analyzed using the ANOVA. The result of this analysis generates a value known as the F statistic, which represents the ratio of the variation between groups within the population being studied. It is generally expected that if the groups come from a single population, then the variation between groups will be less than the variation that is observed among the members of the entire population.
On the hand, a two-way ANOVA involves the calculation of variation between two populations being studied. This statistical approach is generally helpful when more than three populations are being examined during in the research study. The two-way ANOVA thus attempts to determine whether the variation between the groups of each population are the same or different and once this has been established, then the means of each group will then be compared with those of the groups of another population. This statistical approach is therefore beneficial in large-scale studies that involve multi-center subjects or patients, or in other cases, when the samples have been collected from different sites around the country and even around the world. The broader range of approach and the encompassing coverage assists in the analysis of the information collected from the study.
Freedman, D., Pisani, R. & Purves, R. (2007). Statistics, 4th ed. New York: W.W. Norton and Company, 720 pages.
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