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Analyzing the General Social Survey (GSS) in SPSS: Exploring Variables, Attitudes, and Marital Status

Delve into the intricate world of social dynamics and attitudes through the lens of the General Social Survey (GSS) with our comprehensive analysis in SPSS. This in-depth exploration guides you through the examination of various variable types, including nominal, ordinal, and interval ratio variables. Uncover the influence of education on attitudes towards legal access to abortion, providing insight into the complex interplay of societal factors. Additionally, gain an understanding of respondents' marital status distribution, offering a broader context for the analysis of social perspectives. Our study opens doors to a deeper understanding of human interactions and beliefs.

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Problem Description

Explore the social dynamics and attitudes of respondents within the General Social Survey (GSS) dataset. This SPSS assignment focuses on identifying and analyzing various types of variables, from nominal and ordinal to interval ratios. Additionally, it delves into the impact of education on support for pregnant women's legal access to abortion, and examines the marital status distribution among respondents, shedding light on the complex web of factors influencing societal perspectives.

Part A: Exploring Variables in the GSS

Nominal Variables

  1. Abnomore - This variable measures whether a pregnant woman should be legally allowed to obtain an abortion if she is married and wants no more children. [Source: Codebook, Page 5]
  2. Absingle - Measures whether it should be legal for a pregnant woman to obtain an abortion if she is not married and does not want to marry the man. [Source: Codebook, Page 7]

Ordinal Variables

  1. Goodlife - This variable reflects respondents' views on the chances of improving their standard of living in America. It is measured on a five-point Likert scale, ranging from "Strongly agree" to "Strongly disagree." [Source: Codebook, Page 18]
  2. Immameco - Measures respondents' opinions on whether immigrants are generally good for America's economy. It is also measured on a five-point Likert scale, ranging from "Strongly agree" to "Strongly disagree." [Source: Codebook, Page 24]

Interval Ratio Variables

  1. Age - Measures the age of the respondent.
  2. Educ - Represents the highest year of school completed by the respondent.

Part B: Variable Selection and Analysis

Variables Chosen

  1. Absingle - Evaluates support for pregnant women obtaining an abortion if not married and unwilling to marry the man.
  2. Educ - Represents the highest year of school completed by the respondent.

Research Question

How does education affect a person's support for a pregnant woman being legally allowed to obtain an abortion if she is not married and does not want to marry the man?

Hypothesis

Higher education individuals are more supportive of pregnant women being legally allowed to obtain an abortion if they are not married and do not want to marry the man than those with lower education.

Variables Identification

  1. Dependent Variable: Absingle - It is considered the dependent variable because it is influenced by the independent variable, education.
  2. Independent Variable: Educ - Education is assumed to influence one's stance on allowing pregnant women to obtain an abortion.

Explanation

Those with higher education tend to have a broader mindset, which makes them more open to complex and controversial issues like abortion. On the other hand, individuals with lower education may be more inclined to follow traditional beliefs and resist change. This leads to the hypothesis that people with higher education are more supportive of allowing pregnant women to obtain an abortion if they are not married and do not want to marry the man.

Part C: Marital Status Analysis

Variable Description

  1. Marital - This variable reveals the respondent's current marital status, including options such as married, widowed, divorced, separated, or never married.

Type of Variable

  • Marital is a nominal variable as it doesn't have inherent order or numerical significance.

SPSS Output (Sample):

The SPSS output is:

Statistics

MARITAL STATUS

N Valid 1499
Missing 1

MARITAL STATUS

Frequency Percent Valid Percent Cumulative Percent
Valid MARRIED 679 45.3 45.3 45.3
WIDOWED 127 8.5 8.5 53.8
DIVORCED 257 17.1 17.1 70.9
SEPARATED 49 3.3 3.3 74.2
NEVER MARRIED 387 25.8 25.8 100.0
Total 1499 99.9 100.0
Missing NA 1 .1
Total 1500 100.0

Table 1: SPSS Output

Sample Characteristics

  • Total sample size: 1500
  • Only 1 missing value ("NA") in the dataset.
  • 17.1% of the sample is divorced.

 Summary

  • The unmarried category, which includes "Never married," "Widowed," and "Divorced," accounts for 51.4% of the sample.
  • Out of 1499 respondents, 45.3% are married, 25.8% are never married, 3.3% are separated, 8.5% are widowed, and 17.1% are divorced.

This analysis offers a snapshot of respondents' marital status within the GSS dataset, which is essential for understanding how variables like education, attitudes, and demographics interconnect.