QUESTION SThe following table contains yearly data on sales (S) and advertising (A) from 2020 to 2023:S2347Year2020202120222023A24410Where:S: sales (unit);A: advertising (unit).Consider the following simple linear regression: S=B, +B₁A.1. Use Ordinary Least Squares Method to estimate ß, and p₁;2. Interpret the slope;3. Find the prediction line;4. Compute the coefficient of determination; that is, R²;5. What would be the effect of a 3-unit increase in advertising on sales?6. What would be the effect of a 4-unit decrease in advertising on sales?

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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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. Extent of Arctic Sea Ice The National Snow and Ice Data Center monitors the amount of ice in the Arctic year round. The table below gives approximate values for the sea ice extent in millions of square kilometers from 1986 to 2012, in two-year intervals. (a) Make a scatter plot of the data. (b) Find and graph the regression line. (c) Use the linear model in part (b) to estimate the ice extent in the year 2016. Ice extent Ice extent Year (million km?) Year (million km?) 1986 7.5 2000 6.3 1988 7.5 2002 6.0 1990 6.2 2004 6.0 1992 7.5 2006 5.9 1994 7.2 2008 4.7 1996 7.9 2010 4.9 1998 6.6 2012 3.6 Source: National Snow and Ice Data Center
The value of a sports franchise is directly related to the amount of revenue that a franchise can generate. The following data represents the value in 2014 (in $millions) and the annual revenue (in $millions) for the 30 Major League Baseball franchises. Suppose you want to develop a simple linear regression model to predict franchise value based on annual revenue generated. Team Revenue Value Baltimore 245 1000 Boston 370 2100 Chicago White Sox 227 975 Cleveland 207 825 Detroit 254 1125 Houston 175 800 Kansas City 231 700 Los Angeles Angels 304 1300 Minnesota 223 895 New York Yankees 508 3200 Oakland 202 725 Seattle 250 1100 Tampa Bay 188 625 Texas 266 1220 Toronto 226 870 Arizona 211 840 Atlanta 267 1150 Chicago Cubs 302 1800 Cincinnati 227 885 Colorado…
At a large state university, the Statistics department is interested in tracking the progress of its students from entry until graduation. In this example: X represents a student’s final numeric grade (out of 100) in an introductory statistics course Y represents a student’s final numeric grade (out of 100) in an upper-level statistics course The least-squares regression equation for this relationship is: Y = 5.20 + 0.93X What is the slope of the regression line? Provide a numeric value as shown in the equation.
46. Table 1.3 lists the ages and weights of nine girls. TABLE 1.3 Girls' Ages and Weights Age (months) Weight (pounds) 22 19 23 21 24 25 27 28 29 31 31 28 34 32 38 34 43 39 (a) Find the linear regression equation for the data. (b) Find the slope of the regression line. What does the slope represent? (c) Superimpose the graph of the linear regression equation on a scatter plot of the data. (d) Use the regression equation to predict the approximate weight of a 30-month-old girl..
The table lists the average tuition and fees at private colleges and universities for selected years. Year 1985 1990 1995 2000 2008 5311 25,115 Tuition and Fees (in dollars) 9375 SO 12,418 (a) Find the equation of the least-squares regression line that models the data. y 840.450 (Type the slope as a decimal rounded to three decimal places. Round the y-intercept to the nearest integer.) (b) Graph the data and the regression line in the same viewing window using the parameters given below the graph choices. Choose the correct graph below. OA. O B. o HE RO OC. 16,230 A o ƠN
The percentage of adults who smoke in America is given below. Year America 1970 37.4 mon n 1980 33.2 1990 25.3 2000 23.1 2010 19.4 a) Write the linear regression model for A(x), representing the percentage of adult smokers in America x years since 1970. [Use your calculator OR Desmos to find the equation, Round coefficients to the nearest 100"] b) What is the slope of A(x)? Explain its meaning. c) Solve A(x) = 15. Show your work. Explain the meaning of your answer. d) Suppose in 2005, there were approximately 200 million adults in America. Use your model to estimate how many were smokers. Show how you get your answer.
Suppose that a simple linear regression model is appropriate for describing the relationship between y = house price (in dollars) and x = house size (in square feet) for houses in a large city. The population regression line is y = 22,500 + 43x and ?e = 4,000. b) Approximately what proportion of 2,000 sq ft homes would be priced over $110,000? (You may need to use a table. Round your answer to four decimal places.) Approximately what proportion of 2,000 sq ft homes would be priced under $100,000? (You may need to use a table. Round your answer to four decimal places.)
he table shows the minimum wage rates for the United States during different years. Year 1978 1979 1980 1990 1991 1996 1997 2007 2008 2009 Minimum hourly wage ($) 2.65 2.90 3.35 3.80 4.25 4.75 5.15 5.85 6.55 7.25 Write the least squares regression equation that models the data. Let x = time in years since 1900 and let y = minimum hourly wage. Use the equation to estimate the minimum hourly wage of a U.S. worker in 2025. Show your work. Answer:

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