For this Introduction to Quantitative Analysis: Descriptive Analysis Assignment, you will examine the same two variables you used from your Week 2 Assignment and perform the appropriate descriptive analysis of the data given.
To prepare for this Assignment:
· Review this week’s Learning Resources and the Central Tendency and Variability media program.
· For additional support, review the , and the .
· Using the SPSS software, open the Afrobarometer dataset or the High School Longitudinal Study dataset from your Assignment in Week 2.
· Choose the same two variables you chose from your Week 2 Assignment and perform the appropriate descriptive analysis of the data.
· Once you perform your descriptive analysis, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.
Write a 2- to 3-paragraph analysis of your descriptive analysis results and include a copy and paste your output from your analysis into your final document.
Based on the results of your data, provide a brief explanation of what the implications for social change might be. Early in your Assignment, when you relate which dataset you analyzed, please include the mean of the following variables. 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.
Use appropriate APA format, citations and referencing. Refer to the APA manual for appropriate citation.
RESOURCES
· Frankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society (9th ed.). Thousand Oaks, CA: Sage Publications.
· Chapter 3, “Measures of Central Tendency” (pp. 75-111)
· Chapter 4, “Measures of Variability” (pp. 113-150)
· Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.
· Chapter 4, “Organization and Presentation of Information”
· Chapter 11, “Editing Output”
· Wheelan, C. (2013). Naked statistics: Stripping the dread from data. New York, NY: W. W. Norton & Company.
· Skill Builders:
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You are encouraged to click through these and all Skill Builders to gain additional practice with these concepts. Doing so will bolster your knowledge of the concepts you’re learning this week and throughout the course
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