Post a brief introduction in the discussion forum

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Reference no: EM131312736 , Length:

Overview Resources Discussions

To complete the following discussions, go to this week''s Discussion links in the left navigation.

Post Your Introduction

Post a brief introduction in the discussion forum entitled "Post Your Introduction." In your initial post, provide a brief description of your knowledge and/or experience related to business analytics.

Guided Response: Review several of your classmates' introductory posts, and welcome at least three of your peers. Try to respond to peers who have different experiences than you and share how your experiences are different and what you can learn from one another in this course. You are encouraged to post your required replies early during the week to promote more meaningful and interactive discourse in this discussion.

The Modeling Process

We live in the data-driven world. In our personal lives, we are surrounded by websites offering weather or airfare predictions, and in our professional lives we deal with revenue projections and metrics analysis.

Data analysis in the real world is mostly driven by the desire to solve problem(s). In your initial post, share a real-life problem where you have applied (or would like to apply) the seven-step modeling process. Is this problem structured, semi-structured, or unstructured? Explain your decision-making process.

Guided Response: Review several of your classmates' posts and respond to at least two of your peers by 11:59 p.m. on Day 7 of the week. You are encouraged to post your required replies early during the week to promote more meaningful interactive discourse in the discussion. Do you agree with your classmates' decision-making process? Explain why or why not. If your decision-making process would have be different, describe what you would have done differently to solve the problem.

Carefully review the Discussion Forum Grading Rubric for the criteria that will be used to evaluate this Discussion Thread.

Add-ins/Scatterplots/Correlation

Note that this discussion is due on Day 6. Although the initial post is due on Day 6, you are encouraged to start working on it early, as it includes creating a scatterplot in Excel, prior to being able to answer the questions. Prior to beginning work on this assignment, read Chapter 2-4b and 2-4c. In preparation for the course, be sure to have added one or both of the add-ins for Excel. They are the Analysis Toolpak and/or Palisade's StatTool.

Complete Problem 23 in Chapter 3 on page 105.

The file P02_10.xlsx contains midterm and final exam scores for 96 students in a corporate finance course.

Do the students' scores for the two exams tend to go together, so that those who do poorly on the midterm tend to do poorly on the final, and those who do well on the midterm tend to do well on the final? Create a scatterplot, along with a correlation, to answer this question.

Superimpose a (linear) trend line on the scatterplot, along with the equation of the line. Based on this equation, what would you expect a student with a 75 on the midterm to score on the final exam? (Albright, 2017, p. 105).

In the discussion area, answer both questions in Parts a and b. Attach the Excel document that shows the scatterplot, correlation, and trend line.

REFERENCE:

Albright, S. C, & Winston, W. L. (2017). Business Analytics: Data Analysis and Decision Making (6th ed.). Boston, MA: CH 3

Attachment:- Data.xlsx

Verified Expert

This task provides a clear working example of scatter plot, Pearson correlation coefficient and regression analysis. here, the relationship between midterm scores and final exam scores are validated. Data analysis is one of the fields in business and research sectors which showed very fast growth in the recent years. With the use of advanced technologies, the data analysis in the real world has grown extensively to greater heights..

Reference no: EM131312736

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