A study of the top 75 MBA programs attempted to predict the average starting salary (in $1000's) of 6 graduates of the program based on the amount of tuition (in $1000's) charged by the program. The results of a simple linear regression analysis are shown below: Least Squares Linear Regression of Salary Predictor Variables Coefficient Std Error T P Constant 18.1849 10.3336 1.76 0.0826 Tuition 1.47494 0.14017 10.52 0.0000 R-Squared Adj R-Squared 0.5972 0.6027 Resid. Mean Square (MSE) 532.986 Standard Deviation 23.0865 In addition, we are told that the coefficient of correlation was calculated to be r = 0.7763. Interpret this result. A) There is a fairly strong positive linear relationship between the amount of tuition charged and the average starting salary variables. B) There is almost no linear relationship between the amount of tuition charged and the average starting salary variables. C) There is a very weak positive linear relationship between the amount of tuition charged and the average starting salary variables. D) There is a fairly strong negative linear relationship between the amount of tuition charged and the average starting salary variables.

A study of the top 75 MBA programs attempted to predict the average starting salary (in $1000's) of 6 graduates of the program based on the amount of tuition (in $1000's) charged by the program. The results of a simple linear regression analysis are shown below: Least Squares Linear Regression of Salary Predictor Variables Coefficient Std Error T P Constant 18.1849 10.3336 1.76 0.0826 Tuition 1.47494 0.14017 10.52 0.0000 R-Squared Adj R-Squared 0.5972 0.6027 Resid. Mean Square (MSE) 532.986 Standard Deviation 23.0865 In addition, we are told that the coefficient of correlation was calculated to be r = 0.7763. Interpret this result. A) There is a fairly strong positive linear relationship between the amount of tuition charged and the average starting salary variables. B) There is almost no linear relationship between the amount of tuition charged and the average starting salary variables. C) There is a very weak positive linear relationship between the amount of tuition charged and the average starting salary variables. D) There is a fairly strong negative linear relationship between the amount of tuition charged and the average starting salary variables.

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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Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 11,433.70 + 3312.68(Education) + 819.54 (Experience ) Suppose an employee with 7 years of education has been with the company for 5 years (note that education years are the number of years after 8th grade). According to this model, what is his estimated annual salary? 囲 Tables E Keypad Answer Keyboard Shortcuts
A simple regression model for 10 pair of data resulted in a standard error of 3.95 (i.e., Se = 3.95), and the. The sum of squares of error (SSE) is ______. a. 187.23 b. 171.63 c. 156.03 d. 140.42 e. 124.82
Use the pizza cost and the subway fare in the table below to find the regression equation, letting pizza cost be the predictor (x) variable. (Pizza cost is in dollars per slice, subway fare and CPI are in dollars.) What is the best predicted subway fare when pizza costs $3.98 per slice? Year Pizza Cost Subway Fare CPI 1960 1973 1986 1995 2002 2003 2009 2013 2015 2019 0.152 0.353 1.000 1.251 1.753 2.003 2.254 2.300 2.747 2.997 0.151 0.346 1.000 1.347 1.497 2.004 2.253 2.551 2.747 2.750 29.6 44.4 109.6 152.4 180.0 184.0 214.5 233.0 237.0 252.2 The regression equation is y=+x. (Round the y-intercept to four decimal places as needed. Round the slope to three decimal places as needed.) The best predicted subway fare when pizza costs $3.98 per slice is $ (Round to the nearest cent as needed.)
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1. School administrators believe their freshman applications are influenced by two variables: tuition and the size of the applicant pool of eligible high school seniors in the state. The following data for an 8-year period show the tuition rates (per semester) and the sizes of the applicant pool for each year: Tuition in pesos Applicants Pool Applicants 27000 76,200 11,060 37500 78,050 10,900 41250 67,420 8,670 42000 70,390 9.050 46500 62,550 7,400 48750 59,230 7,100 52500 57,900 6,300 57900 60,080 6,100
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Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 10,160.10 +3147.75(Education) + 1230.34(Experience) Suppose an employee with 8 years of education has been with the company for 20 years (note that education years are the number of years after 8th grade). According to this model, what is his estimated annual salary? Answer Tables Keypad Keyboard Shortcuts