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1、 2014 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.Chapter 21. A dependent variable is also known as a(n) _.a. explanatory variableb. control variablec. predictor variabled. response variableAnswer: d
2、Difficulty: EasyBlooms: KnowledgeA-Head: Definition of the Simple Regression ModelBUSPROG: Feedback: A dependent variable is known as a response variable.2. If a change in variable x causes a change in variable y, variable x is called the _. a. dependent variableb. explained variablec. explanatory v
3、ariabled. response variableAnswer: cDifficulty: EasyBlooms: ComprehensionA-Head: Definition of the Simple Regression ModelBUSPROG: Feedback: If a change in variable x causes a change in variable y, variable x is called the independent variable or the explanatory variable.3. In the equation y = + x +
4、 u, is the _.0 1 0a. dependent variableb. independent variablec. slope parameterd. intercept parameterAnswer: dDifficulty: EasyBlooms: KnowledgeA-Head: Definition of the Simple Regression ModelBUSPROG: Feedback: In the equation y = + x + u, is the intercept parameter.0 1 0 2014 Cengage Learning. All
5、 Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.4. In the equation y = + x + u, what is the estimated value of ?0 1 0a. 1 b. +1c. =1()()=1()2d. =1Answer: aDifficulty: EasyBlooms: KnowledgeA-Head: Deriving the Ordinary Least
6、Squares EstimatesBUSPROG: Feedback: The estimated value of is .0 1 5. In the equation c = + i + u, c denotes consumption and i denotes income. What is the residual for 0 1the 5th observation if =$500 and =$475?5 5a. $975b. $300c. $25d. $50Answer: cDifficulty: EasyBlooms: KnowledgeA-Head: Deriving th
7、e Ordinary Least Squares EstimatesBUSPROG: Feedback: The formula for calculating the residual for the ith observation is . In this case, the =residual is =$500 -$475= $25.5=556. What does the equation denote if the regression equation is y = 0 + 1x1 + u?=0+1a. The explained sum of squaresb. The tota
8、l sum of squaresc. The sample regression functiond. The population regression functionAnswer: cDifficulty: Easy 2014 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.Blooms: KnowledgeA-Head: Deriving the
9、Ordinary Least Squares EstimatesBUSPROG: Feedback: The equation denotes the sample regression function of the given regression =0+1model.7. Consider the following regression model: y = 0 + 1x1 + u. Which of the following is a property of Ordinary Least Square (OLS) estimates of this model and their
10、associated statistics?a. The sum, and therefore the sample average of the OLS residuals, is positive.b. The sum of the OLS residuals is negative.c. The sample covariance between the regressors and the OLS residuals is positive.d. The point ( , ) always lies on the OLS regression line.Answer: dDiffic
11、ulty: EasyBlooms: KnowledgeA-Head: Properties of OLS on Any Sample of DataBUSPROG: Feedback: An important property of the OLS estimates is that the point ( , ) always lies on the OLS regression line. In other words, if , the predicted value of .= 8. The explained sum of squares for the regression fu
12、nction, , is defined as _.=0+11+1a. =1()2b. =1()2c. =1 d.=1()2Answer: bDifficulty: EasyBlooms: KnowledgeA-Head: Properties of OLS on Any Sample of DataBUSPROG: Feedback: The explained sum of squares is defined as =1()29. If the total sum of squares (SST) in a regression equation is 81, and the resid
13、ual sum of squares (SSR) is 25, what is the explained sum of squares (SSE)?a. 64b. 56 2014 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.c. 32d. 18Answer: bDifficulty: ModerateBlooms: ApplicationA-Head
14、: Properties of OLS on Any Sample of DataBUSPROG: AnalyticFeedback: Total sum of squares (SST) is given by the sum of explained sum of squares (SSE) and residual sum of squares (SSR). Therefore, in this case, SSE=81-25=56.10. If the residual sum of squares (SSR) in a regression analysis is 66 and th
15、e total sum of squares (SST) is equal to 90, what is the value of the coefficient of determination?a. 0.73b. 0.55c. 0.27d. 1.2Answer: cDifficulty: ModerateBlooms: ApplicationA-Head: Properties of OLS on Any Sample of DataBUSPROG: AnalyticFeedback: The formula for calculating the coefficient of determination is . In this case, 2=12=1 6690=0.2711. Which of the following is a nonlinear regression model?a. y = 0 + 1x1/2 + ub. log y = 0 + 1log x +uc. y = 1 / (0 + 1x) + ud. y = 0 + 1x + uAnswer: cDiffic
