In order to determine the relationship between the number of units sold of a company's product (y) in 9cities with their major competitor's price (*1) in dollars, and the number of stores (r2) the competitor hasin each city, the following data were collected.CompetitorCompetitorUnits soldPriceStores5503535453535404060040260044351035570394650451615453Generate a linear multiple regression output for the data.a) Report the regression coefficients accurate to 3 decimal places:ŷ=b) Report the coefficient of determination accurate to 3 decimal places:R

Given: Number of units sold y = 550 , 545, 540, 600, 600, 510, 570, 650, 615 Competitor price x1=…

In order to determine the relationship between the number of units sold of a company's product (y) in 9 cities with their major competitor's price (x1) in dollars, and the number of stores (x2) the competitor has in each city, the following data were collected. Competitor Price Competitor Stores Units sold 550 35 3 545 35 3 540 40 600 40 600 44 3 510 35 570 39 650 45 1 615 45 3 Generate a linear multiple regression output for the data. a) Report the regression coefficients accurate to 3 decimal places: b) Report the coefficient of determination accurate to 3 decimal places: R =

In order to determine the relationship between the number of units sold of a company's product (y) in 9 cities with their major competitor's price (x1) in dollars, and the number of stores (x2) the competitor has in each city, the following data were collected. Competitor Price Competitor Stores Units sold 550 35 3 545 35 3 540 40 600 40 600 44 3 510 35 570 39 650 45 1 615 45 3 Generate a linear multiple regression output for the data. a) Report the regression coefficients accurate to 3 decimal places: b) Report the coefficient of determination accurate to 3 decimal places: R =

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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An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage, y. The accompanying data represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. Complete parts (a) through (d) below. Click here to view the weight and gas mileage data. ..... (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. x + (Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as needed.) (b) Interpret the slope and y-intercept, if appropriate. Choose the correct answer below and fill in any answer boxes in your choice. (Use the answer from part a to find this answer.) A. For every pound added to the weight of the car, gas mileage in the city will decrease by mile(s) per gallon, on average. A weightless car will get miles per gallon, on average. O B. A weightless car will get miles per gallon, on…
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A major brokerage company has an office in Miami, Florida. The manager of the office is evaluated based on the number of new clients generated each quarter. Data were collected that show the number of new customers added during each quarter between 2015 and 2018. A multiple regression model was developed with the number of new customers as the dependent and the following four independent variables: Period (1, …, 16): A variable that measures the trend; Q1 = 1 for first quarter, Q1 = 0 otherwise; Q2 = 1 for second quarter, Q2 = 0 otherwise; Q3 = 1 for third quarter, Q3 = 0 otherwise. Questions: 1. Explain each of the four slopes (Period, Q1, Q2, Q3). 2. How many new customers would you expect in the second quarter of the following year (2019)?
For major league baseball teams, do higher player payrolls mean more gate money? Here are data for each of the American League teams in the year 2002. The variable x denotes the player payroll (in millions of dollars) for the year 2002, and the variable y denotes the mean attendance (in thousands of fans) for the 81 home games that year. The data are plotted in the scatter plot below, as is the least-squares regression line. The equation for this line is y = 11.43 + 0.23x. Player payroll, x (in Mean attendance, y (in $1,000,000s) thousands) Anaheim 62.8 28.52 Baltimore 56.5 33.09 40- Boston 110.2 32.72 35 Chicago White Sox 54.5 20.74 30- Cleveland 74.9 32.35 25- Detroit 54.4 18.52 Kansas City 49.4 16.30 15- Minnesota 41.3 23.70 10+ New York Yankees 133.4 42.84 Oakland 41.9 26.79 20 40 60 80 100 120 140 Seattle 86.1 43.70 Player payroll, Тarmpa Bay 34.7 13.21 X (in $1,000,000s) Техas 106.9 29.01 Toronto 66.8 20.25 Send data to calculator Send data to Excel Based on the sample data and…
An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage, y. The accompanying data represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. Complete parts (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable.
Used cars 2010 Vehix.com offered several used ToyotaCorollas for sale. The following table displays the ages ofthe cars and the advertised prices. a) Make a scatterplot for these data.b) Do you think a linear model is appropriate? Explain.c) Find the equation of the regression line. d) Check the residuals to see if the conditions for infer-ence are met. Age (yr) Price ($) Age (yr) Price ($)1 15988 6 99951 13988 6 119882 14488 7 89903 10995 8 94883 13998 8 89954 13622 9 59904 12810 10 41005 9988 12 2995
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