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QUESTION 1 - Which one of the statements below is NOT true?

a) Multicollinearity in multiple regression means that variables correlate with each other strongly.

b) Multiple regression expresses the effect of one specific X on Y, while controlling for other Xs.

c) A multiple regression analysis with 4 variables requires a data set of roughly 30 observations.

 

 

QUESTION 2 - Which one of the statements below is NOT true?

a) Homoscedasticity is a desired characteristic of OLS regression functions.

b) In OLS regression, you may use a nominal (preferably dummy) variable as a dependent variable.

c) An R squared of 0.9 tells us that 90% of the variance is explained by the regression function.

 

 

QUESTION 3 - Which one of the statements below is NOT true?

a) Homoscedasticity is a desired characteristic of OLS regression functions.

b) In OLS regression, you may use a nominal (preferably dummy) variable as a dependent variable.

c) An R squared of 0.9 tells us that 90% of the variance is explained by the regression function.

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Question 1:  Which one  of the following statements is NOT true?

                     A - Outliers can have a substantial  impact on the correlation coefficient and should preferably be removed.

                     B - A Correlation coefficient r of -0.2 means that there is a weak negative relationship.

                     C - You can run a correlation analysis with one nominal variable and one parametric variable?

Question 2:  Assume that the true weight of a unit is 100grams.  You measure the weight 6 times with your measurement                         device.  The outcome of the 6 measurements are 90= grams, 89 grams, 90 grams, 91 grams, 90 grams, 90                           grams.  As such, your measurement device is:

                      A - Precise but not accurate

                      B- Accurate but not precise

                      C - Neither accurate nor precise

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