Discussion Questions 1 & 2

DQ #1: 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.

DQ #2: 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.