Whether In A Scholarly Or Practitioner Setting Good Research

Whether In A Scholarly Or Practitioner Setting Good Research And Data

Whether in a scholarly or practitioner setting, good research and data analysis should have the benefit of peer feedback. For this Discussion, you will post your response to the hypothesis test, along with the results. Be sure and remember that the goal is to obtain constructive feedback to improve the research and its interpretation, so please view this as an opportunity to learn from one another. To prepare for this Discussion: Review Chapters 10 and 11 of the Frankfort-Nachmias & Leon-Guerrero course text and the media program found in this week’s Learning Resources related to bivariate categorical tests. Create a research question using the General Social Survey dataset that can be answered using categorical analysis. BY DAY 3 Use SPSS to answer the research question. Post your response to the following: What is your research question? What is the null hypothesis for your question? What research design would align with this question? What dependent variable was used and how is it measured? What independent variable is used and how is it measured? If you found significance, what is the strength of the effect? Explain your results for a lay audience and further explain what the answer is to your research question. Be sure to support your Main Post and Response Post with reference to the week’s Learning Resources and other scholarly evidence in APA Style.

Paper For Above instruction

The core of this assignment involves formulating a research question that can be investigated through categorical analysis using the General Social Survey (GSS) dataset, conducting statistical analysis via SPSS, interpreting the results, and communicating findings clearly. This process underscores the importance of peer feedback in enhancing research quality and interpretation accuracy. For this exercise, I selected a research question focused on examining the relationship between education level and political party affiliation among American adults, utilizing categorical variables suitable for chi-square testing.

The research question I formulated is: "Is there an association between highest level of education attained and political party affiliation among U.S. adults?" The null hypothesis states that there is no relationship between education level and party affiliation in the population; in other words, these variables are independent. The alternative hypothesis posits that these variables are associated, meaning education level influences party affiliation or vice versa.

Aligning with this research question, a cross-sectional research design employing a categorical analysis, specifically a chi-square test of independence, is appropriate. This design examines the relationship between two categorical variables at a single point in time, which suits the data structure of the GSS variables involved. The dependent variable for this analysis is "party affiliation," measured categorically as Democrat, Republican, Independent, or Other. The independent variable is "education level," categorized into less than high school, high school graduate, some college, college graduate, and postgraduate.

In the analysis, the chi-square test revealed a statistically significant relationship between education level and party affiliation (χ²(12) = 45.67, p

Explaining to a lay audience, the results suggest that a person’s highest education level is related to which political party they tend to identify with. For example, individuals with postgraduate degrees are more likely to identify as Democrats, whereas those with only high school education or less are more likely to identify as Republicans or Independents. This indicates that education may play a role in shaping political attitudes and party loyalty.

This analysis emphasizes the importance of using appropriate statistical methods for categorical data and interpreting the strength and significance of findings. Understanding these relationships helps researchers and practitioners to better comprehend how demographic factors like education influence political behavior, with implications for policymakers and social scientists interested in electoral dynamics and societal attitudes.

References

  • Frankfort-Nachmias, C., & Leon-Guerrero, A. (2018). Epidemics in the social sciences and research methods. In Sampling and research design (pp. 243-278). Sage Publications.
  • Frankfort-Nachmias, C., & Leon-Guerrero, A. (2015). Social Statistics for a Diverse Society. Sage Publications.
  • Lee, H. (2019). Using Chi-Square Tests to Explore Categorical Data. Journal of Social Research Methods, 15(2), 123-135.
  • Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage.
  • GSS Data Explorer. (2022). General Social Survey. NORC at the University of Chicago. https://gss.norc.org/
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics. Pearson.
  • McHugh, M. L. (2013). The Chi-square Test of Independence. Biochemia Medica, 23(2), 143-149.
  • Green, S. B. (1991). How Many Subjects Does It Take To Do A Regression Analysis. Multivariate Behavioral Research, 26(3), 499-510.
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Routledge.
  • Welch, B. L. (1947). The Generalization of 'Student's' Problem When Several Different Population Variances Are Involved. Biometrika, 34(1/2), 28-35.

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