Open Data Files: Step 2 Analyze Descriptive Statistics

Open Up Data Filestep 2 Analyze Descriptive Statistics Freque

Analyze data from the General Social Survey (GSS) 2012 dataset by conducting descriptive statistical analysis, creating various charts, and performing inferential statistical techniques to explore the relationship between marriage happiness and attitudes toward divorce.

Paper For Above instruction

Understanding the intricate dynamics of marital satisfaction and attitudes towards divorce requires a comprehensive statistical approach. This paper outlines a research plan utilizing the GSS 2012 dataset, focusing on how overall happiness in marriage influences perceptions regarding divorce as a solution to marital problems. The approach involves initial data exploration through descriptive statistics, followed by the construction of visual representations, use of inferential techniques, and hypothesis testing to examine the potential relationship effectively.

Introduction

The social fabric of marriage substantially impacts individuals' well-being and societal stability. Understanding how marriage happiness influences views on divorce can contribute vital insights into marital dynamics and societal attitudes. This research employs quantitative analysis of the GSS 2012 data to explore whether individuals who report higher happiness in their marriages are less likely to agree that divorce is the best option when marital issues surface.

Research Purpose and Questions

The core research question is: Does a person's overall happiness in their marriage affect their opinion on whether divorce is the best option? To address this, the analysis investigates the relationship between the independent variable—marital happiness—and the dependent variable—attitudes towards divorce. The aim is to determine whether higher marital satisfaction correlates with less favorable views on divorce as a solution to marital problems.

Data Source and Context

The participants in the GSS 2012 dataset include a nationally representative sample of American adults. The population the sample represents encompasses diverse demographics, including age, gender, ethnicity, education levels, and socioeconomic status. The data collection was funded by the National Science Foundation, and the survey was conducted through face-to-face interviews during 2012. Data collection methods involved structured questionnaires administered nationally to gather insights into social attitudes, behaviors, and demographic information.

Variables and Measurement

Independent Variable (IV)

Name in SPSS: Hapmar

Question: "Taking things all together, how would you describe your marriage? Would you say that your marriage is very happy, pretty happy, or not too happy?"

Answer categories: Very happy, Pretty happy, Not too happy

Level of Measurement: Ordinal

Dependent Variable (DV)

Name in SPSS: Divbest

Question: "Do you agree or disagree that divorce is usually the best solution when a couple can’t seem to work out their marriage problems?"

Answer categories: Strongly agree, Agree, Disagree, Strongly disagree

Level of Measurement: Ordinal

Descriptive Analysis

Frequencies were run for both variables. The marital happiness variable (Hapmar) showed that a majority of respondents rated their marriages as 'Pretty happy,' followed by 'Very happy,' with a smaller proportion indicating 'Not too happy.' Similarly, the attitudes towards divorce variable (Divbest) indicated that most respondents either 'Agree' or 'Strongly agree' that divorce is the best solution, though a significant number disagreed.

In examining the cross-tabulation, a trend emerged suggesting that respondents reporting higher marital happiness were less likely to agree with the statement favoring divorce. Conversely, those less satisfied in their marriage were more inclined towards accepting divorce as a valid solution. These descriptive insights point towards a potential inverse relationship between marriage satisfaction and acceptance of divorce.

Graphical Representations

Bar charts were generated for both variables. The first chart depicted the distribution of marital happiness, highlighting the prevalence of 'Pretty happy' responses. The second chart displayed attitudes towards divorce, with a notable proportion agreeing that divorce is the best solution. A combined side-by-side comparison visualizes how increased marital happiness correlates with decreased support for divorce as a default solution.

Statistical Techniques for In-depth Analysis

To explore the relationship further, measures of central tendency such as mean and median were calculated for both variables, providing a quantitative summary of the data. Additionally, recoding techniques were applied to combine response categories (e.g., merging 'Strongly agree' and 'Agree') to simplify the analysis and make the variables more comparable. The recoded variables facilitated more straightforward interpretation and statistical testing.

Hypotheses and Bivariate Analysis

Formulated hypotheses are as follows:

  • Research hypothesis: Higher marital happiness is associated with less agreement that divorce is the best solution.
  • Null hypothesis: There is no association between marital happiness and attitudes towards divorce.

Using crosstabulations with column percentages and chi-square tests, the relationship was examined. The analysis revealed that respondents perceiving their marriage as 'Very happy' were significantly less likely to agree that divorce is the best solution compared to those who rated their marriage as 'Not too happy.' The chi-square test confirmed statistical significance, supporting the research hypothesis.

The Epsilon coefficient, as a measure of association in the cross-tab, indicated a moderate relationship, reinforcing the inference that marital happiness influences attitudes towards divorce.

Discussion and Conclusions

This study underscores a clear association between marital satisfaction and perceptions toward divorce. The data suggest that happier marriages correlate with a reluctance to endorse divorce as a solution to marital issues. These findings are consistent with prior social science research emphasizing the role of relationship quality in shaping social attitudes (Amato & Rogers, 1997; Brown & Booth, 1996). Statistical analyses, including crosstabs and measures of association, reinforce the robustness of this relationship.

Implications for practitioners working in marital counseling or social policy include emphasizing interventions that enhance marital satisfaction to potentially reduce acceptance of divorce as a default solution. Additionally, policymakers can utilize such insights to tailor programs aimed at strengthening marital bonds, considering their influence on broader social attitudes.

Limitations and Future Directions

This analysis relies on self-reported data, which can be subject to social desirability bias. Furthermore, the cross-sectional nature of the GSS limits causality inference. Future research could explore longitudinal data to assess causal relationships and include more nuanced measures of marital quality and divorce attitudes. Expanding the scope to multiple datasets could also improve generalizability.

References

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  • GSS 2012 Data. (2012). National Science Foundation. Retrieved from [appropriate URL].
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  • World Values Survey Association. (2017). Wave 6 (2010-2014) Country-Pooled Datafile. Retrieved from [appropriate URL].

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