If so what is the nature of this relationship in each

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price? If so, what is the nature of this relationship in each case? b. Perform regression analysis on the data. Show each of the regression outputs on a separate sheet in the workbook. Print ONLY the Regression sheet for the model you select after you’ve adjusted the columns so you can read all the written descriptions – on one page! Answer the questions: Would you recommend using both variables together in the model? Explain why you chose the model you did – your explanation must be complete for full points. What is this estimated regression equation (type it out with 2 decimals)? c. How well does your regression model fit the data? Justify your answer. d. Use your estimated regression equation to predict the price of a laptop computer with the following features: a 60-megahertz processor, and 32-megabytes of RAM. Turn in the following (in order): Cover page as always. Summary page with typed answers to all questions (questions are in bold italics: 1c, 2a-d). Be sure to identify your answers as 1c, etc. Other printouts in this order – o Number version of spreadsheet for 1a. o Chart for 1b. o Plots for 2a. o Regression output for 2b. Submit your Excel file (appropriately named per general instructions) in Canvas before class!
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