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Multiple Regression Analysis : Multiple Regression Analysis Of The Sunrise Company

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In this case study three I used the information from the last two assignments to form a report for Sunrise Company that included a multiple regression model, an Interpretation of all the estimated regression coefficients, using the t-test or the p-value, analysis of residuals, and analysis coefficient of Determination (R2) and the F-test. In this scenario I am hired to be a statistical consultant to provide information from a sample of BMW data. In this part Sunrise is requiring a memo based on all the data that I have gathered. I will be gathering my data together to advise Sunrise on how they should market their cars to customers making them more knowledgeable and profitable.
The multiple regression analysis describes how all of the variables compare and relate to one another. In my data I found that y-variables relate to two or more x- variables. The Regression Statistics that I got from my data is that my multiple regression analysis is 0.459078018449413 this predicts how comparable the two variables are. I compared price and mileage of the used BMW. I found that cars with a higher mileage were cheaper than cars with less mileage. This comparison of the qualitative variables shows that for the most part higher mileage means a cheaper car. This is only just an estimate though because there are other factors such as model, color, and age that can contribute to the overall price of the car. These will only slightly increase the value of the car but the same rule follows

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