A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures.ý = 35 + 13z1 + Bzwhere1 = 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 toSclect your answerby $13 for every dollar increase in- Select your answer-vwhen - Select your answeris held constant.b: Sales can be expected toSclect your answerby $6 for every dollar increase inSclect your answer -whenSelect your answeris held constant.-Icon KeyExercise 15.04 Algo (Loast Square Mothod)

here given regression equation y^ = 35 + 13x1 + 5 x2 x1 = inventory investment (in 1000 $) x2 =…

Answered: a. Predict the sales resulting from a…

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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Is the following table created with an exponential or a linear equation? Y 1 10 13 3 16 4 19
Using the regression to model annual income, a variable for years of education has a slope = 2000. This means that the model predicts each additional year of education will yield an extra 2,000 for the average person's salary, regardless of how many total years of education a person has. A. True B. False
Refer to the Baseball 2018 data, which reports information on the 2018 Major League Baseball season. Let attendance be the dependent variable and total team salary be the independent variable. Determine the regression equation and answer the following questions. Click here for the Excel Data Filea-1. Draw a scatter diagram.1. On the graph below, use the point tool to plot the point corresponding to the Attendance and its team salary (Salary 1).2. Repeat the process for the remainder of the sample Salary 2, Salary 3, … ).3. To enter exact coordinates, double-click on the point and enter the exact coordinates of x and y. a-2. From the diagram, does there seem to be a direct relationship between the two variables?multiple choice 1 Yes No b. What is the expected attendance for a team with a salary of $100.0 million? (Round your answer to 4 decimal places.) c. If the owners pay an additional $30 million, how many more people could they expect to attend? (Round your answer to 3…
A biology student is investigating the claim that the temperature can be predicted by counting cricket chirps. She has found a linear regression equation T=42.2+0.21r, where T is the temperature in degrees Fahrenheit and r is the number of chirps per minute. What is the predicted temperature for 90 chirps per minute? 18.9 degrees 227.6 degrees 23.3 degrees 61.1 degrees
Mary used a sample of 68 large U.S. cities to estimate the relationship between Crime (annual property crimes per 100,000 persons) and Income (median annual income per capita, in dollars). Her estimated regression equation was Crime = 428 + 0.050 Income. If Income decreases by 500, we would expect that Crime will Group of answer choices remain unchanged. decrease by 25. increase by 500. decrease by 50.
Use the data shown in the graph to write a quadratic regression equation. Then predict the box office revenue in 2013. Let x represent the number of years since 2000. Millions of dollars 32- 189 31+ 30- Box office revenue 28.9 29.4 28.7 30.8 29- 28- 27- 2004 2005 2006 2007 2008 2009 Year
Choose the correct answer of each number. 1. 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 before in that branch is a. $417,750 b. $341,250 c. $376,700 d. $335,6502. 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…
A regression analysis between sales ( Y in $1,000 ) and advertising (X in $1,000) resulted in the following equation = 14,200 + 2.6 X The above equation implies that … … an increase of $ 14,200 in advertising is associated with an increase of $ 14,200 in sales … an increase of $ 1,000 in advertising is associated with an increase of $ 14,200 in sales … an increase of $ 2,600 in advertising is associated with an increase of $ 1,000 in sales … an increase of $ 1,000 in advertising is associated with an increase of $ 2,600 in sales
A teacher wants to form a linear regression equation to predict a student's score on the final based on the number of hours they spent studying for it. Final scores are in percents. y=2x + 60 R-Squared = 0.65 What does the y-intercept mean in terms of the situation? O If a student doesn't study for the final, their score on the final would be 60%. O If they doesn't study for the final their score would be 65%. O The student should study for the final. O A ripe Mango. O If a student doesn't study for the final, their score would be 2%.
2. Participants were kept awake for a certain number of hours before given a visuospatial task. Researchers measured how many correct responses each participant had. Results are shown below. Use alpha = .01. Number of Correct Hours Kept Awake (X) Responses (Y) 21 X = 10 SS, = 422 Y = 10 SS, = 690 2 4 19 %3D 6. 13 SPxy =-525 ху 5 20 S, =5.70 S, = 7.29 9. 11 10 9. 14 5 15 5 17 2 18 1 17 1 13 4 18 8 11 A. Graph the data. B. State the hypotheses. C. Make a decision about the null. a. Calculate Pearson's r i. Decision about null hypothesis? b. Calculate effect size i. Interpret effect size. D. State your conclusion. E. Relate your conclusion to the research. F. Calculate the regression formula. G. If someone was kept awake for 9 hours, what is the predicted number of correct responses?
A. Develop an estimated regression equation that can be used to predict the price of the stock based on the number of shares of company's stocks sold and the volume of exchange. B. Interpret the coefficients of the estimated regression equation that you found in Part a. C. If in a given day, the number of shares of the company that were sold was 94,500 and the volume of exchange on the New York Stock Exchange was 16 million, what would you expect the price of the stock to be?
An automotive sales manager wishes to examine the relationship between age (years) and sales price ($) for used automobiles of a certain brand. The accompanying table contains data for a sample of a certain make and model that were listed for sale at a car shopping website. b. Fit a quadratic regression model to predict price and state the quadratic regression equation.

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