One-way ANOVA in Practice
- Search for a quantitative article related to one-way ANOVA Testing
- Something in the area relating to Public Policy or Justice Administration.
- Write a (2 pages only) critique.
- Include: Why the authors used One-way ANOVA test, was it appropriate, did the authors display the data, does results stand alone.
One-way ANOVA in Practice
One-way ANOVA is conventionally used by researchers to examine the relationship between variables. One-way ANOVA is almost similar to independent samples t-test. However, the independent samples t-test does not have the option to perform post hoc tests and can only compare two factors with the dependent sample. This essay examines an article in which one-way ANOVA was used to determine whether there is a statistically significant relationship between safety and security index and human development.
Sow, MT (2014) analysed data from 53 African countries with regard to safety and security index and human development. The research carried out by the author indicated that human development is important as a determinant of the achievement or national development. Employee motivation and the resulting turnover and retention rates are driven by safety and security, as well as human development. The author intended to examine whether levels of safety and security affect personal development. Safety and security measures were divided into two groups, those with low safety and security scores and those with high scores (Sow, 2014).
The null hypothesis stated that there is no statistically significant relationship between safety and security index and human development index. The alternative hypothesis stated that the relationship between safety and security index and human development index is statistically significant. The author obtained data from the Index of African Governance available at the National Bureau of Economic Research website. The author stated that the ANOVA was used because it has the possibility of carrying out post-hoc tests for controlling type 1 error, and because it compares more than two factors as compared to t-tests. One-way ANOVA was an appropriate test considering the nature of the data analysed. For the analysis, the author set participants with scores of safety and security lower than the mean as Low SS and the others were referred as the High SS group, SS being Safety and Security (Sow, 2014).
The researcher required the p-value to be less than 0.05 for the relationship to be statistically significant. However, the p-value was 0.25, which is larger than 0.05. Therefore, contrary to the author’s conclusion, the ANOVA was not significant F(1 510 = 5.36, p= 0.25. There was not enough evidence to reject the null hypothesis and conclude that the safety and security index is significantly related to human development. The effect size was also relatively low, 0.28, implying that safety and security factor only accounted for 28% of the variance of human development (Sow, 2014).
The results of the analysis indicated that there is no statistically significant relationship between social and security index and human development index. The authors displayed all the relevant data and the output of the analysis that are effective in displaying the results of the study simply and clearly. Apart from the tables for the output data, the author has also used a diagram to indicate the difference in the means for the two variables. The results do not, therefore, stand alone, but are adequately illustrated by a box plot and tables (Sow, 2014). There are two shortfalls to the report, however. The author has rejected the null hypothesis yet the p-value is greater than 0.05, and has also not shown the strength of the relationship between the two groups, low SS and high SS, by providing the significance values from the post-hoc tests.
though the results indicated that there is no statistically significant
relationship between safety and security index and human development index, the
relationship between the two would be meaningful. When people feel that they
are safer and more secure, they tend to attain higher human development. This
is one case in which the p-value shows that there is no statistically
significant relationship between variables while in reality, the relationship
is meaningful. The study results can help in improving human development index
by ensuring increased safety and security levels for all individuals.
Sow, M.T. (2014). Using ANOVA to Examine the Relationship between Safety & Security and Human Development. Journal of International Business and Economics, 2(4): 101-106.