Posted: October 20th, 2022

When you paste the dataset, make sure the first row includes all variable names and no white space in any of the names.

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In this assignment, you are expected to complete a small case study by building a linear regression model based on your own dataset. You can use any dataset you find interesting to you. Ideally, the dataset is real and from your work (do ask for permission from your employer). There are two requirements for the dataset used in this case study:
It should contain one attribute as the “target” variable you want to predict for (e.g., Revenue) and two or more attributes that can be reasonable “predictor” variables used to predict the target variable. For example, “Direct Labor Cost” and “Direct Expenses” are two variables that can be reasonably used to predict “Revenue”. But “Number of Rocks on the Moon” is not a reasonable predictor for predicting revenue.
The number of records (i.e., the number of rows) in your dataset should be equal to or larger than 5 * the number of predictors in order to produce reliable modeling outcomes. For example, if your dataset has five predictors, there should be 25 or more records in the dataset.
Meanwhile, although not a requirement, it is ideal that you use a business dataset in this case study.
Download and open the Excel VBA program file for the linear regression analysis from HERE. The “Data Sources” tab in the file is blank. Please copy and paste into this tab your dataset. When you paste the dataset, make sure the first row includes all variable names and no white space in any of the names. Meanwhile, there should be no missing values in any of the columns under the variable names.
Then, please complete a simple case study report using the attached report template. After you complete the report, upload both the report file and the Excel VBA program file containing your data and model results.

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