STAT 3704 Bonus Homework Due Monday, Dec

STAT 3704 Bonus HW This bonus homework is due on Monday, Dec 3rd midnight

This bonus homework is due on Monday, December 3rd at midnight. All work must be performed using JMP software. The outputs generated from JMP must be included in your submission, and each output should be accompanied by a clear, brief explanation in plain English that describes what the output represents and how it relates to the analysis.

Answer the following questions:

Question 1:

Question 2:

Question 3:

Question 4:

Paper For Above instruction

For this assignment, students are required to utilize JMP, a statistical analysis software, to analyze datasets pertinent to the questions posed. The primary goal is to demonstrate proficiency in using JMP to perform statistical procedures, interpret the results accurately, and communicate findings effectively through plain English explanations.

When approaching each question, students should first identify the appropriate statistical method or test relevant to the problem context. For example, if comparing means across multiple groups, ANOVA might be suitable; for assessing relationships, regression analysis could be appropriate; for distributions, histogram or normality tests may be used. After performing the analysis in JMP, students must include the generated output—such as tables, graphs, or test results—and accompany each with a concise paragraph explaining the significance of the output and how it addresses the question at hand.

Ensuring clarity and accuracy in explanations is vital. This means avoiding technical jargon unless necessary, and when used, it should be briefly defined. The goal is to communicate findings to an audience that may not have expertise in statistics, emphasizing the practical implications of the results.

Overall, this assignment emphasizes the integration of practical software skills with analytical thinking and clear communication. By thoroughly analyzing the data, correctly interpreting JMP outputs, and articulating insights in plain language, students will demonstrate their comprehensive understanding of statistical analysis methods pertinent to the course.

References

  • SAS Institute. (2021). JMP Statistical Discovery Software. SAS Institute Inc.
  • Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. Sage publications.
  • Agresti, A., & Finlay, B. (2009). Statistical Methods for the Social Sciences. Pearson.
  • Moore, D. S., McCabe, G. P., & Craig, B. A. (2014). Introduction to the Practice of Statistics. W.H. Freeman.
  • Zimmerman, D. W. (1997). The use of the analysis of variance in educational research. Educational and Psychological Measurement, 57(4), 519-540.
  • Wasserman, L. (2004). All of statistics: A concise course in statistical inference. Springer Science & Business Media.
  • Johnson, R. A., & Wichern, D. W. (2007). Applied Multivariate Statistical Analysis. Pearson.
  • Everitt, B. S. (2002). An R & S interpretive guide to multivariate analysis. Wiley.
  • Rencher, A. C., & Schaalje, G. J. (2008). Methods of Multivariate Analysis. John Wiley & Sons.
  • Wilkinson, L. (1999). Statistical methods in education and psychology. Annual Review of Psychology, 50, 265-287.

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