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ADMS 2320 (42)
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Ch16.doc

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Department
Administrative Studies
Course
ADMS 2320
Professor
Douglas Kong
Semester
Winter

Description
CHAPTER 16 SIMPLE LINEAR REGRESSIONAND CORRELATIONSECTIONS 12MULTIPLE CHOICE QUESTIONSIn the following multiplechoice questions please circle the correct answery1The regression line 32x has been fitted to the data points 4 8 2 5 and 1 2 The sum of the squared residuals will bea7b15c8d22ANSWERd2If an estimated regression line has a yintercept of 10 and a slope of 4 then when x2 the actual value of y isa18b15c14dunknownANSWERdy3Given the least squares regression line5 2xathe relationship between x and y is positivebthe relationship between x and y is negative8990Chapter Sixteencas x increases so does ydas x decreases so does yANSWERb4A regression analysis between weight y in pounds and height x in inches resulted in ythe following least squares line1205xThis implies that if the height is increased by 1 inch the weight on average is expected toaincrease by 1 poundbdecrease by 1 poundcincrease by 5 poundsdincrease by 24 poundsANSWERc5A regression analysis between sales in 1000 and advertising in 100 resulted in the yfollowing least squares line 75 6xThis implies that if advertising is 800 then the predicted amount of sales in dollars isa4875b123000c487500d12300ANSWERb6A regression analysis between sales in 1000 and advertising inresulted in the yfollowing least squares line 800005xThis implies that anaincrease of 1 in advertising is expected on average to result in an increase of 5 in salesbincrease of 5 in advertising is expected on average to result in an increase of 5000 in salescincrease of 1 in advertising is expected on average to result in an increase of 80005 in salesdincrease of 1 in advertising is expected on average to result in an increase of 5000 in salesANSWERd7Which of the following techniques is used to predict the value of one variable on the basis of other variablesaCorrelation analysisbCoefficient of correlationcCovariancedRegression analysisANSWERd8The residual is defined as the difference betweenathe actual value of y and the estimated value of ybthe actual value of x and the estimated value of x Simple Linear Regression and Correlation 91cthe actual value of y and the estimated value of xdthe actual value of x and the estimated value of yANSWERa9In the simple linear regression model the yintercept represents theachange in y per unit change in xbchange in x per unit change in ycvalue of y when x0dvalue of x when y0ANSWERc10In the first order linear regression model the population parameters of the yintercept and the slope are estimated respectively bybba and 01bbb and 01bbc and 01bbd and 01ANSWERa11In the simple linear regression model the slope represents theavalue of y when x0baverage change in y per unit change in xcvalue of x when y0d average change in x per unit change in yANSWERb12In regression analysis the residuals represent theadifference between the actual y values and their predicted valuesbdifference between the actual x values and their predicted valuescsquare root of the slope of the regression linedchange in y per unit change in xANSWERa13In the firstorder linear regression model the population parameters of the yintercept and the slope are respectivelybba and 01bbb and 01bbc and 01bbd and 01ANSWERd14In a simple linear regression problem the following statistics are calculated from a yyxxxyssample of 10 observations2250105075 xThe least squares estimates of the slope and yintercept are respectivelya15 and 05
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