Exhibit 13-5 Below you are given a partial Minitab output based on a sample of 25 observations. $\begin{array}{lcc}&\text { Coefficient }&\text { Standard Error }\\ \text { Constant } & 145.321 & 48.682 \\ \mathrm{X}_{1} & 25.625 & 9.150 \\ \mathrm{X}_{2} & -5.720 & 3.575 \\ \mathrm{X}_{3} & 0.823 & 0.183 \end{array}$ -Refer to Exhibit 13-5. We want to test whether the parameter ?? is significant. The test statistic equals

A) 0.357 B) 2.8 C) 14 D) 1.96 A) 0.357 B) 2.8 C) 14 D) 1.96

Exhibit 13-6 Below you are given a partial computer output based on a sample of 16 observations. $\begin{array}{lcc} & \text { Coefficient } & \text { Standard Error } \\ \text { Intercept } & 12.924&4.425\\ \mathrm{X}_{1} & -3.682&2.63. \\ \mathrm{X}_{2} &45.216&12.560\\ \end{array}$ $\text { Analysis of Variance }$ $\begin{array}{lccc} \text { Source of } & \text { Degrees } &\text { Sum of } &\text { Mean }\\ \text { Variation } & \text { of Freedom }&\text { Squares } & \text { Square }&F\\ \text { Regression }&&4,853&2,426.5\\ \text {Error }&&&485.3 \end{array}$ -Refer to Exhibit 13-6. Carry out the test to determine if there is a relationship among the variables at the 5% level. The null hypothesis should

A) be rejected B) not be rejected C) revised D) None of these alternatives is correct. A) be rejected B) not be rejected C) revised D) None of these alternatives is correct.

Exam 13: Multiple Regression

Exhibit 13-10 In a regression model involving 30 observations, the following estimated regression equation was obtained. $\hat { Y }$ =170+34X1 - 3X2+8X3+58X4+3X5 For this model, SSR = 1,740 and SST = 2,000. -Refer to Exhibit 13-10. The p-value for testing the significance of the regression model is

(Multiple Choice)

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(37)

Question 141

Exhibit 13-5 Below you are given a partial Minitab output based on a sample of 25 observations. Coefficient Standard Error Constant 145.321 48.682 25.625 9.150 -5.720 3.575 0.823 0.183 -Refer to Exhibit 13-5. We want to test whether the parameter ?? is significant. The test statistic equals

(Multiple Choice)

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(42)

Question 142

Exhibit 13-6 Below you are given a partial computer output based on a sample of 16 observations. Coefficient Standard Error Intercept 12.924 4.425 -3.682 2.63. 45.216 12.560 $\text { Analysis of Variance }$ Source of Degrees Sum of Mean Variation of Freedom Squares Square F Regression 4,853 2,426.5 Error 485.3 -Refer to Exhibit 13-6. Carry out the test to determine if there is a relationship among the variables at the 5% level. The null hypothesis should

(Multiple Choice)

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Question 143

Exhibit 13-9 In a regression analysis involving 25 observations, the following estimated regression equation was developed. $\hat { Y }$ =10 - 18X1+3X2+14X3 Also, the following standard errors and the sum of squares were obtained. Sb₁ = 3 Sb2 = 6 Sb3 = 7 SST = 4,800 SSE = 1,296 -Refer to Exhibit 13-9. The p-value for testing the significance of the regression model is

(Multiple Choice)

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Question 144

Exhibit 13-10 In a regression model involving 30 observations, the following estimated regression equation was obtained. $\hat { Y }$ =170+34X1 - 3X2+8X3+58X4+3X5 For this model, SSR = 1,740 and SST = 2,000. -Refer to Exhibit 13-10. The p-value for testing the significance of the regression model is

Exhibit 13-5 Below you are given a partial Minitab output based on a sample of 25 observations. Coefficient Standard Error Constant 145.321 48.682 25.625 9.150 -5.720 3.575 0.823 0.183 -Refer to Exhibit 13-5. We want to test whether the parameter ?? is significant. The test statistic equals

Data and Statistics

Descriptive Statistics: Tabular and Graphical Displays

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Comparisons Involving Means, Experimental Design, and Analysis of Variance

Comparisons Involving Proportions and a Test of Independence

Simple Linear Regression

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