A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures.i25+10z + 8where1= inventory investment ($L000s)I2= advertising expenditures ($1000s)y= sales ($1000s)The data used to develop the model came from a survey of 10 stores; for those data, SST= 18,000 and SSR – 11,000.a. Compute SSE, MSE, and MSR (to 2 decimals, if necessary).SSE -MSE -MSR -b. Use an F test and o = 0.05 level ofificancedetermine whether there is a relationship among the variables.Compute F test statistic (to 2 decimals). Use F table.The p-value isScicct your answer -What is your conclusion?ThereSeicct your answer - V a significant relatioriship attiuiu tLHe variatles.

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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 researcher wanted to predict the sodium content (in milligrams) of beef hot dogs by looking at the calorie content. His findings from a sample of 10 beef hot dogs are summarized below. The regression equation for his data is ŷ= -299.48 + 4.35 x Calories 186 181 176 149 184 190 158 139 175 148 Sodium 495 477 425 322 482 587 370 322 479 375 Interpret the slope in terms of this problem. If appropriate, find the sodium content if the calorie content is 170. If not, why? If appropriate, find the sodium content if the calorie content is 136. If not, why?
The price (in Tk.) and demand (in kg) of a product is given in the following table: Price (Tk.) 25 37 40 45 48 50 55 70 Demand (kg) 10 8 9 7.5 4.5 3 2 a. Determine the coefficient of correlation between the two variables. Answer rounded to three decimal places. b. Determine the slope coefficient B1 for the regression of Demand on Price. Answer rounded to three decimal places. c. Determine the y-intercept Bo for the regression of Demand on Price. Answer rounded to two decimal places. d. What will be the demand when price is Tk. 52? Answer rounded to two decimal places. LO
The datasetBody.xlsgives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (lb), Height (in), and circumference (cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist. We are interested in predicting body fat based on abdomen circumference. Find the equation of the regression line relating to body fat and abdomen circumference. Make a scatter-plot with a regression line. What body fat percent does the line predict for a person with an abdomen circumference of 110 cm? One of the men in the study had an abdomen circumference of 92.4 cm and a body fat of 22.5 percent. Find the residual that corresponds to this observation. Bodyfat Abdomen 32.3 115.6 22.5 92.4 22 86 12.3 85.2 20.5 95.6 22.6 100 28.7 103.1 21.3 89.6 29.9 110.3 21.3 100.5 29.9 100.5 20.4 98.9 16.9 90.3 14.7 83.3 10.8 73.7 26.7 94.9 11.3 86.7 18.1 87.5 8.8 82.8 11.8 83.3 11 83.6 14.9 87 31.9 108.5 17.3…
You are the Filipino analyst hired by the multinational company to study the sales data of its more than 75 stores worldwide. You used regression analysis to predict $ sales (y) by using $ advertising (x1) and $ salary of sales representatives (x2) across all the branches. You obtained the following regression function: y = 7800 + 8.5x1-1.6x2 If the advertising budgets of one of the branches of the corporation is now $45,000 (which is 10% more than before) and the salary of sales representatives is now $8,500 (which is 20% less than before), then the predicted sales before in that branch is A. $376,700 B. $335,650 C. $417,750 D. $341,250
For the relationship between Calories and Carbs, here is the equation of the line of best fit: Regression Equation: Calories = 2.36 + 4.432 Carbs What would you predict for the number of Calories if a cereal had 28 Carbs?
An analyst hired by the multinational company to study the sales data of its more than 75 stores worldwide. Used regression analysis to predict $ sales (y) by using $ advertising (x1) and $ salary of sales representatives (x2) across all the branches. You obtained the following regression function: y = 7800 + 8.5x1-1.6x2. If the advertising budgets of one of the branches of the corporation is now $45,000 (which is 10% more than before) and the salary of sales representatives is now $8,500 (which is 20% less than before), then the predicted sales will a. increase by more than 10% b. increase by less than 10% c. decrease by less than 10% d. be the same
A supermarket has a chain of 12 stores in Kuwait. Sales figures and profits for the stores are given in the following table. Obtain a regression equation for the data, and predict profit for a store assuming sales of $20 million. Show all calculations in detail. Sales, x (in millions of dollars) Profits, y (in millions of dollars) 7 0.12 2 0.1 6 0.13 12 0.15 14 0.25 16 0.2 10 0.24 12 0.2 14 0.27 20 0.15 7 0.34 8 0.17
The following data show the brand, price ($), and the overall score for six stereo headphones that were tested by a certain magazine. The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is ŷ = 22.391 + 0.326x, where x = price ($) and y = overall score. Brand Price ($) Score A 180 76 B 150 71 C 95 63 D 70 56 E 70 40 F 35 24 #1) Compute SST, SSR, and SSE. (Round your answers to three decimal places.) SST = SSR = SSE = #2) Compute the coefficient of determination r2.(Round your answer to three decimal places.) r2 = #2a) Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) A) The least squares line provided a good fit as a small proportion of the variability in y has been explained by the least squares line. B) The least squares line provided a good fit as a large…
You are the Filipino analyst hired by the multinational company to study the sales data of its more than 75 stores worldwide. You used regression analysis to predict $ sales (y) by using $ advertising (x1) and $ salary of sales representatives (x2) across all the branches. You obtained the following regression function: y = 7800 + 8.5x1-1.6x2 If the advertising budgets of one of the branches of the corporation is the same as before and the salary of sales representatives is now 20% less than before, then the predicted sales in that branch will A. increase B. no sufficient information to determine C. decrease D. remain the same
The City of Bellmore’s police chief believes that maintenance costs on high-mileage police vehicles are much higher than those costs for low-mileage vehicles. If high-mileage vehicles are costing too much, it may be more economical to purchase more vehicles. An analyst in the department regresses yearly maintenance costs (Y) for a sample of 200 police vehicles on each vehicle’s total mileage for the year (X). The regression equation finds: Y = $50 + .030X with a r2 of .90 What is the IV? What is the DV? If the mileage increases by one mile, what is the predicted increase in maintenance costs? If a vehicle’s mileage for the year is 50,000, what is its predicted maintenance costs? What does an r2 of .90 tell us? Is this a strong or weak correlation? How can you tell?
A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures. ý = 35 + 13z1 + Bz where 1 = inventory investment ($1000s) I2 = advertising expenditures ($1000s) y=sales ($1000s) a. Predict the sales resulting from a $15,000 investment in inventory and an advertising budget of $10,000. b. Interprel b1 and ba in this estimated regression equation. b: Sales can be expected to Sclect your answer by $13 for every dollar increase in - Select your answer- vwhen - Select your answer is held constant. b: Sales can be expected to Sclect your answer by $6 for every dollar increase in Sclect your answer - when Select your answer is held constant. -Icon Key Exercise 15.04 Algo (Loast Square Mothod)

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