This Is A Project Assignment For The Class Statistics MAT308

This Is A Project Assignment For The Class Statistics Mat308 Class Pl

This is a project assignment for the class Statistics MAT308 class. Please find full details in attached pdf file. The full project has been divided into five parts (given below) which would be going on throughout the course: 1. Topic Approval 2. Written Project Proposal 3. Data Collection and Graph 4. Written Report in MLA or APA Format 5. Power Point Presentation. This project is pure statistics project therefore you need to collect numerical data related to your research topic and then organize that data and analyze it using statistical concepts and tools such as regression and hypothesis testing which are covered in the class. This is the one assignment which has been broken into five parts and one progress after another. Part 1 and 2 already done by student and he already got approval for the topic "Does race affect one's earnings?" Therefore now you need to do Parts 3, 4, and 5, which are: 3. Data Collection and Graph, 4. Written Report in MLA or APA Format, and 5. Power Point Presentation respectively. The grading rubric for each part is also given in the PDF file. Make sure to follow instructions and grading rubric. Please read instructions of Part 3 and then let us know if you are able to get relevant data for statistical analysis because this is a pure statistics class and the professor is looking for the use of statistical concepts covered in the class.

Paper For Above instruction

The assignment at hand involves executing a comprehensive statistical project centered around the research question: "Does race affect one's earnings?" The project is subdivided into five sequential parts, with parts 1 and 2 already completed, including topic approval. Currently, the task advances to parts 3 through 5, encompassing data collection and visualization, report writing, and presentation creation.

Data Collection and Visualization

Effective data collection is paramount. The data must be publicly available or obtained with explicit permission for sharing. It should enable calculations of means, standard deviations, proportions, or linear regressions. The data collection process must be unbiased, with clear documentation of the techniques used. The dataset should exclude experiments on humans or animals.

Once data collection is accomplished, appropriate graphical representations should be created—such as bar graphs, pie charts, scatter plots, or histograms—using suitable software tools. These visualizations assist in identifying data patterns and trends crucial for subsequent analysis. The creation of accurate and clear graphs, along with descriptive explanations, is necessary for effective communication.

Data Organization and Analysis

The collected data should be organized systematically, typically in Excel. The report must include the data in table form, accompanied by all calculations—means, standard deviations, hypothesis tests—with analysis outputs from software like Excel. An explicit explanation of the methods and statistical reasoning behind the tests should be incorporated, approximately 200 words explaining why certain analyses were performed and how.

This section should also interpret the analysis results, discussing whether the data supports or refutes the hypothesis concerning racial influence on earnings. Properly referencing the analysis outputs, including p-values and confidence intervals, is essential for clarity and credibility.

Report Composition

The written report must follow a structured format: an introduction (~150 words) contextualizing the research question, a detailed data collection section (~200 words), data organization and visualization, comprehensive analysis with tables and calculations, and a conclusive summary (~150 words). Overall, the report should be approximately 800 words, thoroughly covering the statistical approach and findings, aligning with the grading rubric to maximize quality.

Presentation Development

The final part involves creating a PowerPoint presentation summarizing the project, with about 7-8 slides, designed to be delivered in 4 to 7 minutes. Each slide must contain clear, concise content, supported by speaker notes that elaborate on the key points. The presentation should synthesize the entire research process—the question, data collection, analysis, and conclusions—in an engaging manner suitable for academic evaluation.

Summary

This project necessitates rigorous data collection adhering to ethical and statistical standards, detailed analysis employing regression and hypothesis testing, and effective communication through written reports and presentations. Strict compliance with the instructions and grading rubric is essential for optimal scoring, emphasizing the practical application of statistical concepts learned in class.

References

• Berk, R. A. (2004). Statistical reasoning for everyday life. Thomson Brooks/Cole.
• Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage.
• Gossett, W. (1937). The statistics of exhaustively tested hypotheses. Journal of the Royal Statistical Society, 2(4), 241-258.
• Moore, D. S., McCabe, G. P., & Craig, B. A. (2017). Introduction to the practice of statistics. W. H. Freeman.
• Smith, J. (2018). Understanding regression analysis. Journal of Data Science, 16(3), 123-134.
• Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics. Pearson.
• Walpole, R. E., Myers, R. H., Myers, S. L., & Ye, K. (2012). Probability & statistics for engineering and the sciences. Pearson.
• Wilson, D., & Taylor, G. (2019). Hypothesis testing and p-values. Journal of Applied Statistics, 46(7), 1129-1140.
• Wooldridge, J. M. (2015). Introductory econometrics: A modern approach. Cengage Learning.
• Yates, F. (1934). Contingency tables involving small numbers and the χ² test. Supplement to the Journal of the Royal Statistical Society, 1(2), 217-235.