A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures.ŷ = 21 + 10x, + 7x2%DwhereX1inventory investment ($1,000s)advertising expenditures ($1,000s)X2sales ($1,000s).y =(a) Predict the sales (in dollars) resulting from a $15,000 investment in inventory and an advertising budget of $10,000.(b) Interpret b1and b, in this estimated regression equation.2.Sales can be expected to increase by $for every dollar increase in inventory investment when advertising expenditure is held constant. Sales can be expected to increase by$for every dollar increase in advertising expenditure when inventory investment is held constant.

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Answered: A shoe store developed the following…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A regression analysis between cost to build a clinic (in dollars) and clinic size (in square foot) resulted in the following equation: y=75+6x. This implies that if the clinic size is 800 square feet, then the cost to build a clinic (in dollars) is?
You are conducting a multiple regression analysis to determine if there is a linear relationship between y, the number of applications to in-state universities and two factors: ×1, the state's unemployment rate and ×2, the average grant provided to in-state students. Ten observations are available. The analysis produced the estimated regression equation below. y = 6.5 + 2.2×1 + 4.6×2 The standard error for the intercept, unemployment rate are 9.34, and 1.23, respectively. Is the coefficient for the unemployment rate variable statistically significant at the 5% significance level? Explain. A) No, since stat = 1.39 for this coefficient, which is less than 2.365. B) No, since the p-value for this coefficient is .072, which is greater than 05 C) None of these D) No, since the p-value for this coefficient is .072, which is greater than .05
people eat cereal as a daily source of fiber, and these cereals contain the mineral potassium. Suppose a linear model was made to predict a cereal's potassium content using its fiber content, and suppose the model had intercept 37 and slope 25. For a cereal having 270 milligrams and 18 grams of fiber, what is the residual (in mg)?
What is the slope and intercept for the regression equation given this data?X = -5, 34, 56, 0, 61Y = 13, 63, 46, -23, 50
The table shows the average weekly wages (in dollars) for state government employees and federal government employees for 8 years. The equation of the regression line is y=1.410x−17.174. Complete parts (a) and(b) below.
After interviewing salespersons at Harley Davidson dealerships, a researcher has created a linear regression line to explain the relationship between a Harley Davidson motorcycle's age (x) and price (y). The regression has an R² = 87.7%. Write a sentence summarizing what R² says about this regression. The age of the motorcycle explains 12.3% of the variation in price. The age of the motorcycle explains 9.36% of the variation in price. The age of the motorcycle explains 87.7% of the variation in price. The price of the motorcycle explains 12.3% of the variation in age. The price of the motorcycle explains 87.7% of the variation in age.
A sports-equipment researcher was interested in the relationship between the speed of a golf club (in feet per second) and the distance a golf ball travels (in yards). Information was collected on several golfers and was used to obtain the regression equation ŷ = 2x - 106, where x represents the club speed and ŷ is the predicted distance. Which statement best describes the meaning of the slope of the regression line? For each increase in distance by 1 yard, the predicted club speed increases by 2 ft/sec. For each increase in distance by 1 yard, the predicted club speed decreases by 106 ft/sec. For each increase in club speed by 1 ft/sec, the predicted distance increases by 2 yards. For each increase in club speed by 1 ft/sec, the predicted distance decreases by 106 yards.
The volume (in cubic feet) of a black cherry tree can be modeled by the equation y=−50.8+0.3x1+5.1x2, where x1 is the tree's height (in feet) and x2 is the tree's diameter (in inches). Use the multiple regression equation to predict the y-values for the values of the independent variables.
A student used multiple regression analysis to study how family spending (y) is influenced by income (X1), family size (x2), and additions to savings (x3). The variables y, x1, and x3 are measured in thousands of dollars. The following results were obtained.
A business analyst found a linear relationship between the predicted profit (in thousands of dollars) with the amount of employees hired (think of the units as per person). The resulting regression equation and coefficient of determination were found to be: ŷ = 10 + 4.5x R² = 72% a) Interpret the slope and y-intercept using the guidelines learned in class. b) Find the predicted profit when the you hire 5 employees. c) Suppose that the true profit when 5 employees are hired is $42 thousand dollars. Find the residual. d) What is the correlation coefficient? Round to three decimal places. e) What is the strength of the correlation coefficient?
What's true about the first differences and slope for a linear equation?
The table shows the total square footage (in billions) of retailing space at shopping centers and their sales (in billions of dollars) for 10 years. The equation of the regression line is y = 516.388x - 1699.161. Complete parts a and b. Total Square Footage, X Sales, y 4.9 5.1 5.2 5.4 5.6 5.7 ********** (a) Find the coefficient of determination and interpret the result. 5.9 5.8 (Round to three decimal places as needed.) How can the coefficient of determination be interpreted? 5.9 883.3 937.6 986.3 1059.5 1107.2 1200.9 1281.1 1340.8 1438.2 1536. 6.2 OA. The coefficient of determination is the fraction of the variation in sales that can be explained by the variation in total square footage. The remaining fraction of the variation is unexplained and is due to other factors or to sampling error. OB. The coefficient of determination is the fraction of the variation in sales that is unexplained and is due to other factors or sampling error. The remaining fraction of the variation is…

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