This Week You Will Continue Working On The Second Part Of It

This Week You Will Continue Working On The Second Part Of The Lab Tha

This week, you will continue working on the second part of the lab that serves as your major project. You are expected to apply the feedback received on the first lab of this project from Week 6 in your final submission. Your tasks include running basic analyses, creating graphs, and reporting and discussing your results. Referencing Chapters 13, 14, and 16 of your textbook will be helpful for completing this lab. You will revise and report both the previous information and new data, following APA format for the Methodology, Results, and Discussion sections.

Make sure to use the cleaned data provided, which includes the t-test tabs that were shared after you submitted your cleaned datasheet. The submission should include both the written report and the Excel sheet with the analysis and the completed code key. Utilize the Week 7 Lab Instructions RSM802_Week 7 Lab Instructions.docx as the template and detailed guide for your report.

For executing the independent sample t-tests, you may choose to use SPSS, Jamovi, or Excel. Specific instructions and tutorials are available, including a video demonstrating the process in SPSS and a starting point at 2:16 in a tutorial for Excel. Both Excel and SPSS have dedicated tabs to help you create the necessary graphs by entering summary data. Using the graphs tab in Excel may simplify the process.

Your completed assignment, including the report, analysis, and code, is due by the end of Sunday. Ensure your work adheres to APA style and incorporates proper analysis and discussion of your findings.

Paper For Above instruction

The second part of the laboratory project aims to deepen the analysis of the data through statistical testing, visualization, and comprehensive reporting within an APA-format manuscript. Building upon the foundational work from Week 6, students are expected to perform independent sample t-tests, generate appropriate graphs, and interpret the results in the context of the research question. The use of specific statistical software—SPSS, Jamovi, or Excel—is flexible, each offering tools suitable for t-test execution and visualization. Attention to APA formatting ensures clarity and professionalism in the presentation of methodology, results, and discussion sections.

To begin, students should utilize the cleaned dataset provided, which includes pre-prepared t-test tabs for straightforward analysis. This dataset is designed to streamline the process of performing the required statistical tests and creating corresponding visualizations. Once the analysis is complete, interpretation of the results involves assessing statistical significance, effect sizes, and possible implications of the findings. The graphs generated should clearly depict group differences or relationships uncovered through the analysis, enriching the report's discussion.

Methodologically, the paper should describe the data preparation, test assumptions, and statistical procedures in accordance with APA guidelines, citing the relevant chapters from the textbook. In the Results section, reporting should include test statistics, degrees of freedom, p-values, and effect sizes, supported by visual aids. The Discussion should interpret the findings, situating them within the broader research context, discussing limitations, and suggesting future directions.

Students should submit both the written report in APA format and the Excel file containing the analysis output and code. The deadline is specified as Sunday evening, emphasizing timely completion. This task integrates statistical skills with scholarly reporting, reinforcing students' competence in data analysis and scientific communication.

References

  • Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage.
  • Gravetter, F. J., & Wallnau, L. B. (2017). Statistics for the behavioral sciences. Cengage Learning.
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Routledge.
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics. Pearson.
  • Laerd Data. (2017). Independent samples t-test in SPSS explained. Laerd.com.
  • IBM SPSS. (2020). Statistics software documentation. IBM.
  • Jamovi Project. (2022). jamovi (Version 1.8) [Computer software].
  • Microsoft Corporation. (2021). Excel (Version 2106) [Computer software].
  • American Psychological Association. (2020). Publication manual of the American Psychological Association (7th ed.).
  • Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage.

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