Business
Business, 07.10.2019 20:10, Lianabel0517

Amanager has estimated a simple linear regression model with an explanatory variable (amount spent on advertisement in thousands of dollars) and a response variable (sales in thousands of dollars). further assume that he has checked the assumptions and all four assumptions seem reasonable. the estimated model is the following: predicted sales (thousands of dollars) = 100+9x (where x = amount spent on advertisement in thousands of dollars).some additional information: the range of the values of the explanatory variable are between $10,000 and $150,000, the median of the explanatory is 82 thousand dollars and the sample mean of the explanatory variable is 76 thousand dollars. the range of values for the response variable are between 30 thousand dollars and 1500 thousand dollars, the median of the response variable is 780 thousand dollars and the sample mean of the response variable is 784 thousand dollars . the rsquared values is 0.89.the narrowest prediction interval for sales at an individual store occurs when the store spends thousand dollars on advertisement. a manager has estimated a simple linear regression model with an explanatory variable (amount spent on advertisement in thousands of dollars) and a response variable (sales in thousands of dollars). further assume that he has checked the assumptions and all four assumptions seem reasonable. the estimated model is the following: predicted sales (thousands of dollars) = 100+9x (where x = amount spent on advertisement in thousands of dollars).some additional information: the range of the values of the explanatory variable are between $10,000 and $150,000, the median of the explanatory is 82 thousand dollars and the sample mean of the explanatory variable is 76 thousand dollars. the range of values for the response variable are between 30 thousand dollars and 1500 thousand dollars, the median of the response variable is 780 thousand dollars and the sample mean of the response variable is 784 thousand dollars . the rsquared values is 0.89.the narrowest prediction interval for sales at an individual store occurs when the store spends thousand dollars on advertisement.

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Business, 23.07.2019 00:20, ayoismeisalex
In 2011 home prices and mortgage rates dropped so low that in a number of cities the monthly cost of owning a home was less expensive than renting. the following data show the average asking rent for 10 markets and the monthly mortgage on the median priced home (including taxes and insurance) for 10 cities where the average monthly mortgage payment was less than the average asking rent (the wall street journal, november 26–27, 2011). city rent ($) mortgage ($) atlanta 840 539 chicago 1062 1002 detroit 823 626 jacksonville, fla. 779 711 las vegas 796 655 miami 1071 977 minneapolis 953 776 orlando, fla. 851 695 phoenix 762 651 st. louis 723 654 a. develop a scatter chart for these data, treating the average asking rent as the independent variable. does a simple linear regression model appear to be appropriate? b. use a simple linear regression model to develop an estimated regression equation to predict the monthly mortgage on the median priced home given the average asking rent. construct a plot of the residuals against the independent variable rent. based on this residual plot, does a simple linear regression model appear to be appropriate? c. using a quadratic regression model, develop an estimated regression equation to predict the monthly mortgage on the median-priced home, given the average asking rent. d. do you prefer the estimated regression equation developed in part a or part c? create a plot of the linear and quadratic regression lines overlaid on the scatter chart of the monthly mortgage on the median-priced home and the average asking rent to you assess the two regression equations. explain your conclusions
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