Linear Regression and Solver Analysis

Linear Regression and Solver Analysis

Learning Goal: I’m working on a excel exercise and need an explanation and answer to help me learn.

Exercise 01: RFM Analysis

Watch this video on RFM analysis. According to techtarget.com, RFM analysis is a marketing technique used to quantitatively rank and group customers based on the recency, frequency and monetary total of their recent transactions to identify the best customers and perform targeted marketing campaigns. Using your own dataset, execute an RFM analysis and explain your analysis and your findings in 500 words or more. Submit a Word document with screenshots of your work and your discussion and also submit the excel dataset that is used while submitting.

Exercise 02: Linear Regression

Open the attached .csv file and select Regression from the data analysis tab on excel.
Weight will be our predictor variable and MPG the response variable. Select your x (predictor) and y (response) ranges accordingly. Check the labels button and output cell.
Observe the ANOVA matrix. The F-statistic will tell you whether your model is better than simply using the mean. You will want the F-statistic to be as high as possible and the significance to be as low as possible.
The equation of the regression (or trend) line provides the relationship between x and y. The coefficient of x tells you how much y will change for each change in x by multiplying the coefficient times the change in x.
To see the linear model, insert a scatter chart. Right click on the chart to open a dialog window that will allow you to add data as you did before for x (predictor) and y (response).
Move your pointer over the chart and select the + symbol at the top right. Select Axis titles and input Weight and MPG where appropriate. Provide a meaningful name for the chart title.
When your mouse is over the + symbol scroll down, check the Trendline box and the More Options button. Select the Linear Model, display the equation on the chart, and show R squared.
You should see a scatterplot roughly bisected by a negative line revealing the weight and MPG are negatively correlated.
Create a linear model with a data set of your own choosing. Discuss, in 500 words or more, the meaning each value in the ANOVA matrix. Interpret the graph, discussing whether the predictor variable does a good job predicting the response and use the ANOVA results in your explanation. Be sure to include a few words about the F statistic relative to the mean because the mean is a commonly used predictor. Submit a Word document with screenshots of your work and your discussion and also submit the excel dataset that is used while submitting.

Exercise 03: Solver

Watch this video. Using your own problem find an optimization solution. Maybe you want to maximize the profit of your sewing operation that makes pants and shirts. Maybe you want to find the optimum balance of stocks in your portfolio. Or, maybe you want to come up with your own example. Submit a Word document with screenshots of your work and your discussion and also submit the excel dataset that is used while submitting.

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