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MU Data Analysis Project

MU Data Analysis Project

Description

Project Parts

Part 1: Descriptive Statistics (100 points)

*Complete this assignment only right now; parts 2, 3, 4, 5, and 6 are future assignments.

Part 2: Inferential Statistics (100 points)

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

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Part I Descriptive Statistics (100 points)

You need to prepare a single workbook that summarizes and charts data you feel is relevant to understanding the characteristics of your data set. This is an intentionally open-ended assignment similar to what you might receive in industry. This is real world data that has not been cleansed. Therefore, it may be necessary to remove observations (rows) that seem inappropriate or modify your data structure for analysis. Document any data elements your removed and note why by cutting and pasting them below the original data table. Then add a comment after the item summarizing your justification for removing the data.

  1. Create a new worksheet called D1. Summarize a single quantitative characteristic and use any descriptive statistic that you feel is useful in presenting the data, including summary measures, pivot table reports, and charts. 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?).
  2. Create a new worksheet called D2. Summarize a single qualitative characteristic and use any descriptive statistic that you feel is useful in presenting the data, including summary measures, pivot table reports, and charts. 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?).
  3. Create a new worksheet called D3. Summarize a single quantitative or qualitative characteristic and use any descriptive statistic that you feel is useful in presenting the data, including summary measures, pivot table reports, and charts. 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?).

Make sure to format the sheets and contents appropriately (remember to label the tabs) and consistently to communicate your summary to your audience. You are summarizing, so avoid too much information.

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