This project takes what we learned in the previous weeks and builds upon it to apply the concepts and techniques to a data set.
This project takes what we learned in the previous weeks and builds upon it to apply the concepts and techniques to a data set.
You only have to complete ONE project. However, each project is slightly different based on the type of data. Therefore, I recommend downloading all of the data sets so that you can learn from these other data sets as we discuss all of the projects in class.
The project is broken up into five parts that you will submit at different times during the 8-week session. Each assignment will build off of the previous assignment; therefore, I recommend staying with the same project for the entire session.
Project Parts
Part 1: Descriptive Statistics (100 points) Use the findings from your Part 1 to complete Part 2.
Part 2: Inferential Statistics (100 points) This assignment is covered in detail here. Complete only this part now.
Part 3: Hypothesis Testing (100 points)
Part 4: Regression Modelling (100 points)
Part 5: Data Visualization (100 points)
Part 6: Presentation (50 points)
Project Options
Session Project – Cyber Security Data.xlsx
Session Project – Sales and Demographics Data.xlsx
Session Project – Sport Management Data.xlsx
Session Project – Stock Market Data.xlsx
Part 2 Inferential Statistics (100 points)
Add the following new sheets to the workbook you submitted for Part 1 of the session project.
Create a new worksheet called I1 in which you create at least one confidence interval each for the mean value of a quantitative characteristic. Add a text box to describe the contents (why did you select this characteristic, why it is important) and the conclusions (what did the data show?).
Create a new worksheet called I2 in which you create at least a confidence intervals for the proportion of a categorical (qualitative) characteristic. Add a text box to describe the contents (why did you select this characteristic, why it is important) and the conclusions (what did the data show?).
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