Walden University Testing for One Way ANOVA Discussion

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Walden University


Now it is time to put all of that good practice to use and answer a social research question with the one-way ANOVA. As you head into the assignment, be sure and pay close attention to the assumptions of the test. Specifically, make sure the dependent and independent variables (factor) are amenable to use in the ANOVA (i.e., be sure to note levels of measurement).

For this Assignment, you will examine the one-way ANOVA based on a research question.

To prepare for this Assignment:

  • Review this week’s Learning Resources and media program related to one-way ANOVA testing.
  • Using the SPSS software, open the Afrobarometer dataset or the High School Longitudinal Study dataset (whichever you choose) found in the Learning Resources for this week.
  • Based on the dataset you chose, construct a research question that can be answered with a one-way ANOVA.
  • Once you perform your one-way ANOVA analysis, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.

For this Assignment:

Write a 2- to 3-paragraph analysis of your one-way ANOVA results for your research question. If you are using the Afrobarometer Dataset, report the mean of Q1 (Age). If you are using the HS Long Survey Dataset, report the mean of X1SES. Do not forget to evaluate if the assumptions of the test are met. Include any post-hoc tests with an analysis of the strength of any relationship found (effect size). Also, in your analysis, display the data for the output. Based on your results, provide an explanation of what the implications of social change might be.

Use proper APA format, citations, and referencing for your analysis, research question, and display of output.

Frankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society (9th ed.). Thousand Oaks, CA: Sage Publications.

  • Chapter 11, “Analysis of Variance” (pp. 373-399)

Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.

  • Chapter 10, “Analysis of Variance”
  • Chapter 11, “Editing Output” (previously read in Week 2, 3, 4, 5. and 6)

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Explanation & Answer

Attached. Please let me know if you have any questions or need revisions.

The research question of interest was with regards to whether there is a significant difference in
the infrastructure index among various regions of Africa. To investigate the research question, a
one-way ANOVA test was used. A one-way ANOVA test was used is it is most appropriate to
test the differences in means for multiple independent populations (Frankfort, 2020). A one-way
ANOVA was therefore computed in SPSS based on the Afrobarometer dataset. The variables of
interest were Country by region (COUNTRY.BY.REGION) and Infrastructure Index
(INFRASTRUCTURE (higher scores=greater infrastructure)). For the dataset the mean value
for age, Q1, was 37.01.
Before the analysis could be carried out, assumptions required to run the ANOVA were first
tested. Assumption required to be met for a one-way ANOVA are; Each sample should be
obtained from a population that is normally distributed, variance equality of all groups, sample
independence, and the dependent variable should be continuous (Singh, 2007). Based on the
boxplot shown in figure 1 of the appendix, there does not appear to extreme deviation from the
normal, and the sample from each group is large. The normality assumption is therefore met. The
homogeneity of variances assumption is not met as results give sufficient evidence that variances
are unequal. Other assumptions are however met as data from each respondent is independently
obtained and the dependent variable, infrastructure index, is continuous.
The analysis was still carried out in SPSS. The results of the analysis were statistically
significant. The result showed that there was sufficient evidence that there is a significant
difference in the infrastructure index among various regions of Africa. F(3,8330) = 80.764,
p=0.000. However, the strength of effect or difference between the regions was small as
indicated by the eta squared value of 0.028. The post hoc analysis showed that there were

significant differences in infrastructure index among all the regions apart from West Africa and
East Africa. However, the difference is not meaningful as depicted by the small effect size. As
one of the ANOVA assumptions was not met, other applicable test...

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