Estimate of the variance in a regression model

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Reference no: EM13243471

1. All of the following are assumptions of the error terms in the simple linear regression model except :
A. Errors are normally distributed
B. Error terms have a mean of zero
C. Error terms have a constant variance
D. Error terms depend on the explanatory variable

2. The point estimate of the variance in a regression model is 
A. SSE
B. MSE
C. se
D. b1

3. The least squares regression line minimizes the sum of the 
A. Sum of Differences between actual and predicted Y values
B. Sum of Squared differences between actual and predicted X values 
C. Sum of Absolute deviations between actual and predicted X values
D. Sum of Absolute deviations between actual and predicted Y values
E. Sum of Squared differences between actual and predicted Y values

4. The ___________ the R2 and the __________ the s (standard error), the stronger the relationship between the dependent variable and the independent variable. 
A. Higher, lower
B. Lower, higher
C. Lower, lower
D. Higher, higher

5.  In simple bivariate regression analysis, if the correlation coefficient is a positive value, then 
A. The Y intercept must also be a positive value.
B. The coefficient of determination can be either positive or negative, depending on the value of the slope.
C. The least squares regression equation could either have a positive or a negative slope.
D. The standard error of estimate can either have a positive or a negative value.
E. The slope of the regression line must also be positive.

6. A researcher wants to explore the relationship between the grades students receive on their Midterm test and their Final test score. The following data present the Midterm and Final scores for ten students. What is the correlation coefficient?

Mid

Fin

180

280

195

280

210

300

225

316

240

320

255

350

255

370

264

320

265

400

290

350



A. 0.556
B. 0.645
C. 0.738
D. 0.802
E. 0.905

Reference no: EM13243471

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