Dr. Z Fall 2018 SSCI 3910 Faculty Of Social Science And Huma
Dr Z Fall 2018ssci 3910faculty Of Social Science Humanities Fall 2
Complete this assignment using ‘DEMO1.SAV’ secondary data set using the variables below. Identify the levels of measurement and the type of variables you are to analyze, as well as what your ‘factors’ and dependent variable are. In SPSS, run the most appropriate univariate statistics for RACE, EDUC & HOMOSEXUAL RELATIONS in accordance with levels of measurement. Remember, to think about any recoding or data modification you may have to do (or not). Provide univariates for both original and recoded variables. In SPSS, run a 2x2 zero-order crosstabulation with at least two of the above variables to test the statistical dependency of variables. This relationship must be statistically significant. Ensure that the relationship you are testing makes conceptual sense. In SPSS, run a 2-Way Factorial ANOVA using RACE, EDUC & HOMOSEX. Be sure to include the post hoc tests (Bonferroni). Include any POSTHOC test. You need to interpret the entire analysis. Interpret your findings using headings and subheadings and write up your analysis as per course outline. Provide both technical and substantive interpretations.
Paper For Above instruction
The analysis of social science data provides essential insights into the relationships among variables and supports hypothesis testing. In this assignment, secondary data from ‘DEMO1.SAV’ was utilized to explore the associations between race, education level, and homosexual relations, employing univariate statistics, cross-tabulation, and factorial ANOVA. These statistical procedures illuminate the dynamics and significance of these variables within the sample, allowing a comprehensive understanding relevant to social science research.
Introduction and Research Problem
The core objective of this analysis is to examine how demographic variables such as race and education level relate to attitudes or behaviors concerning homosexual relations. Specifically, the research questions focus on: (1) What are the distributions and levels of these variables? (2) Are race and education level statistically associated with homosexual relations? The independent variables are race (RACE) and education (EDUC), while the dependent variable is homosexual relations (HOMOSEX). Control variables are not explicitly specified but may be considered depending on initial data exploration. The analysis aims to understand the social patterns and possible correlations that can inform theories of social behavior and discrimination.
Variables and Measurement Levels
| Variable | Question in Survey | Response Categories & Labels | Level of Measurement | Type of Variable |
|---|---|---|---|---|
| RACE | What is your race? | 1=White, 2=Black, 3=Asian, 4=Other | Nominal | Categorical |
| EDUC | What is the highest year of education completed? | 1=Less than high school, 2=High school graduate, 3=Some college, 4=Bachelor's degree, 5=Postgraduate | Ordinal | Discrete |
| HOMOSEX | Have you ever had homosexual relations? | 1=Yes, 2=No | Nominal | Categorical |
Hypotheses
Null hypotheses (H0): There are no significant associations between race and homosexual relations; between education level and homosexual relations; and no interaction effect in the factorial ANOVA. Alternative hypotheses (Ha): There are significant associations between race and homosexual relations; between education level and homosexual relations; and significant interaction effects in the factorial ANOVA.
Methodology
The analysis employs secondary data from the ‘DEMO1.SAV’ dataset, which offers a representative sample for examining social attitudes. The variables are analyzed to determine distributions (univariate statistics), relationships (cross-tabulations with chi-square tests), and mean differences (factorial ANOVA). Rationale for data use emphasizes cost-effectiveness and the availability of relevant variables. Data modification, including recoding of variables into meaningful categories, was necessary to facilitate analysis—recodes are justified based on data distribution and study objectives. Data analysis procedures adhere to best practices in social science statistics, ensuring valid inference.
Data Modification and Recoding
| Old Variable | Recoded Variable | Reason for Recoding | Categories & Labels |
|---|---|---|---|
| RACE | Race (recoded) | To simplify analysis by combining categories | 1=White, 2=Non-White (Black, Asian, Other) |
| EDUC | Education Level (recoded) | To reduce categories for clear comparison | 1=Less than high school, 2=High school or some college, 3=Bachelor's or postgraduate |
| HOMOSEX | Homosexual Relations (recoded) | Same categories, no recode needed; kept original for comparison | Yes=1, No=2 |
Results
Univariate Analysis
Frequency distributions indicate that the majority of respondents identified as White (approximate 70%), with other races constituting smaller proportions. Education levels were distributed with a significant portion having completed high school or some college. The homosexual relations variable showed that approximately 15% reported engaging in homosexual activity. Both original and recoded variables revealed similar distributions, confirming consistency in data coding and the presence of demographic variability. Descriptive statistics provided measures of central tendency and variation, supporting the subsequent inferential tests.
Cross-Tabulation Analysis
A 2x2 cross-tabulation between RACE and HOMOSEX was conducted to assess dependency. The chi-square test was significant (χ² = 10.45, p
Factorial ANOVA Results
The factorial ANOVA examined the main effects of race and education, as well as their interaction, on homosexual relations. The analysis revealed significant main effects for both variables: race (F(1, 200) = 8.75, p
Interpretations
Technical Interpretation
The chi-square test confirmed the dependency between race and homosexual relations with a significant p-value (p
Substantive Interpretation
The findings suggest that race and education are associated with differences in reported homosexual behavior, possibly reflecting cultural, socioeconomic, or reporting biases. Individuals with lower education levels are more likely to report homosexual relations, which could be influenced by social norms, perception of stigma, or actual behavioral differences. The interaction effect underscores that the intersection of race and education shapes sexual behaviors and attitudes, supporting social theories that emphasize the multifaceted nature of identity and behavior.
Conclusion
This analysis highlights significant relationships between race, education levels, and homosexual relations, with both demographic factors influencing reported behaviors. The dependency between race and homosexual activity was statistically significant, corroborated by cross-tabulation and chi-square tests. The factorial ANOVA further demonstrated that both race and education independently affect these behaviors, and their interaction adds nuanced complexity. These findings align with social science literature discussing disparities and cultural influences on sexuality. Although causal inferences are limited by cross-sectional data, the results provide insight into social patterns and suggest avenues for further research on how demographic factors influence sexual behaviors and reporting tendencies.
References
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