Complete The Following Assignment By Filling In All Requests

Complete The Following Assignment By Filling In All Requested Informa

Complete the following assignment by filling in all requested information. In this assignment, you will review mock studies and analyze data within each study. You will need to CAREFULLY follow the directions outlined in each section of the attached document using SPSS. Some of the studies require you to enter data and some require you to use the GSS data set. You will list the five steps of hypothesis testing for each Mock Study to see how every question should be formatted. You will decide whether to reject or fail to reject the null hypothesis based on the two-tailed p value. Be sure to cut and paste the appropriate SPSS outputs under each problem and interpret the outputs within the context of each mock study. Use a different (legible) color font for your responses. NOTE: All calculations should be coming from your SPSS. Hand calculation IS not accepted. You are also required to submit the SPSS output file (*.spv) to get credit for this assignment. This .spv file should include ALL your outputs. In other words, continue to save your output file as you conduct each analysis.

Paper For Above instruction

Introduction

The process of hypothesis testing is fundamental within statistical analysis, especially in research studies involving data collection and interpretation. This assignment requires a comprehensive review of mock studies where data analysis using SPSS is central. The goal is to evaluate and interpret statistical outputs to determine the validity of null hypotheses, emphasizing the critical role of p-values in decision-making.

Understanding the Assignment

The core of this assignment revolves around analyzing mock research studies that incorporate either manually entered data or data sets from the General Social Survey (GSS). For each study, the five steps of hypothesis testing must be meticulously documented. These steps are: stating the hypotheses, setting the significance level, selecting the appropriate statistical test, analyzing SPSS output, and making a decision regarding the null hypothesis.

Deciding whether to reject or fail to reject the null hypothesis depends on the two-tailed p-value obtained from SPSS. A p-value below the significance threshold (commonly 0.05) suggests rejecting the null hypothesis, indicating a statistically significant result. Conversely, a p-value above this threshold supports failing to reject the null, implying that the data do not provide sufficient evidence against it.

The outputs from SPSS—such as t-tests, chi-square tests, or ANOVAs—must be carefully pasted into the document in different colors for clarity, with thorough interpretations provided for each study. Additionally, the assignment requires submitting an SPSS output file (*.spv) containing all analyses conducted during this process.

Methodology

For each mock study, the procedure involves:

  1. Identifying the variables and the research question
  2. Inputting data into SPSS or selecting the appropriate GSS dataset variables
  3. Choosing and executing the proper statistical test based on the data type and research question
  4. Extracting the output results and copying them into the document in distinct colors
  5. Interpreting these results in the context of the study, particularly focusing on p-values and decision rules

Throughout the analysis, it is essential to adhere strictly to the outlined steps, ensuring each stage provides clear reasoning aligned with statistical best practices.

Results and Interpretation

For each mock study, after performing the statistical test in SPSS, the corresponding output must be assessed. The critical value or p-value guides the conclusion:

- If p

- If p ≥ 0.05, fail to reject H0

Interpretations should consider the study context, discussing whether the data support the alternative hypothesis or indicate no significant effect. Inferences about the population based on sample data are central here, emphasizing the importance of the p-value in hypothesis testing.

Conclusion

This assignment highlights the systematic process of hypothesis testing using SPSS, emphasizing critical thinking in interpreting statistical results. The accurate application of the five steps and proper report of outputs are vital for sound research conclusions. Proper documentation and submission of the *.spv file ensure transparency and reproducibility of the analyses.

References

  • Field, A. (2013). Discovering statistics using IBM SPSS Statistics. Sage Publications.
  • Gravetter, F. J., & Wallnau, L. B. (2016). Statistics for the behavioral sciences. Cengage Learning.
  • IBM Corp. (2023). IBM SPSS Statistics for Windows, Version 28.0. Armonk, NY: IBM Corp.
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics. Pearson.
  • Levine, D. M., Stephan, D. F., Krehbiel, T. C., & Berenson, M. L. (2018). Statistics for managers using Microsoft Excel. Pearson.
  • Warner, R. M. (2013). Applied statistics: from bivariate through multivariate techniques. Sage Publications.
  • O’Connell, A. (2011). Research methods (3rd ed.). Nelson Education.
  • McHugh, M. L. (2012). Interrater reliability: the kappa statistic. Biochemia Medica, 22(3), 276-282.
  • Morling, B. (2017). Research methods in psychology. WW Norton & Company.
  • Cooper, H., & Schindler, P. (2014). Business research methods. McGraw-Hill Education.

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