4.. A furniture store owner has several outlets throughout the country, but would like toexpand even more. She selected a random sample of 15 of her existing stores togenerate a least squares regression equation to predict mean daily sales in dollars.She used annual median income in the region measured in thousands of dollars (X1),store area measured in thousands of square feet (X2) and the unemployment rate(measured as a %) in the region (X3) as her independent variables.The estimated least squares regression equation is:Y' = 830 + 12.8 X1 + 0.77 X2 - 35 X3Predict mean daily sales for a region with annual median income of $48000, squarefootage of 12000 and an unemployment rate of 5%. Round your answer to theNEAREST DOLLAR (no decimal places!) Do NOT type the $ sign.I13°C C

From the output, the regression equation is, Y'=830+12.8X1+0.77X2-35X3 Given that X1=48000=48…

Answered: A furniture store owner has several…

Trigonometry (MindTap Course List)

8th Edition

ISBN:9781305652224

Author:Charles P. McKeague, Mark D. Turner

Publisher:Charles P. McKeague, Mark D. Turner

Chapter4: Graphing And Inverse Functions

Section: Chapter Questions

Problem 6GP: If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use...

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Similar questions

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To determine the effectiveness of group study sessions, a college instructor gathers data on hours of attendance and exam scores for students in the class. Which variable, hours of attendance or exam scores, would be the response variable for a least-squares regression equation? is it hours of attendance or exam scores?
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A chemical company, seeking to study the effect of extraction time on the efficiency of an extraction operation, obtained the data from a table: Fit a straight line to the data given with the least squares method and use it to predict the extraction efficiency that would be expected when the extraction time is 35 minutes. x = Extraction time (minutes)y = Extraction efficiency (%)
What are the Assumptions of Extended Least Squares in the Multiple Regression Model?
A year-long fitness center study sought to determine if there is a relationship between the amount of muscle mass gained y(kilograms) and the weekly time spent working out under the guidance of a trainer x(minutes). The resulting least-squares regression line for the study is y=2.04 + 0.12x A) predictions using this equation will be fairly good since about 95% of the variation in muscle mass can be explained by the linear relationship with time spent working out. B)Predictions using this equation will be faily good since about 90.25% of the variation in muscle mass can be explained by the linear relationship with time spent working out C)Predictions using this equation will be fairly poor since only about 95% of the variation in muscle mass can be explained by the linear relationship with time spent working out D) Predictions using this equation will be fairly poor since only about 90.25% of the variation in muscle mass can be explained by the linear relationship with time spent…
find the equation of the least squares regression line
Suppose a least-squares regression line is given by y=4.302x−3.293. What is the mean value of the response variable if x=20? μy20=_______? (Round to one decimal place as needed.)
Above, a table was created to calculate the coefficients of the linear regression y=ax+b model for a data set using the least squares method. What is the coefficient a in this model?
A regression analysis between weight (y in pounds) and height (x in inches) resulted in following least squares line: y^= 120+5x. this implies that if the height is increased by 1 inch, the weight is expected ?

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