Please write about 4 pages with MLA format. . Follow the requirement below, and there is a decision tree ppt.and sample essay was attached for your reference. Thank you very much!!!! Requirement: Based on methods and tools you learned in this course, conduct a project for a realistic application of quantitative analysis to your business or personal decisions. The term paper for this project should include: (1) A one-page description of your problem and its importance (10%). (2) A one-page discussion of the solution procedure and the rationale (10%) (3) One or more pages of presentation of your results (40%) (4) One or more pages of discussion of your insights, critique, and possible expansion for the application (40%). The term paper will be subjectively evaluated by the instructor on the basis of - Originality and relevance of the problem - Clarity and accuracy of the problem formulation - Correctness of the results -Depth of insights from the experience and creativity in the expansion of the application.

A program admissions coordinator wanted to know if the math placement test given to a certain cohort of students was an indicator of how well they would perform on their first exam. She records the scores of their placement test and the first exam and then runs a regression test in JASP shown below. Is there a correlation between these measures? Placement Exam 1 11 49 27 71 7 60 33 85 28 80 23 75 20 61 48 100 35 71 26 81 Pearson's Correlations Variable Placement Exam 1 1. Placement Pearson's r — p-value — 2. Exam 1 Pearson's r 0.876 *** — p-value < .001 — * p < .05, ** p < .01, *** p < .001

Write a 700- to 1,050-word reflective essay about your experience applying quantitative analysis methods and the knowledge you have gained from this course. This should be a professional paper with citations to support your work. Topics of each week five-stage iterative process graphical representation of data measures of central tendency. Mean,Median,Mode Measure of Variation Normal Distribution. Table Relationships Sampling Designs Confidence Intervals. Estimation Errors.