Question 1

Consider the following distribution data for a random variable X: What is the mean and variance of X?

A3.6 and 7.15

B3.4 and 3.84

C3.5 and 3.45

DNone of these

Answer : D

Question 2

Which of the following is a false statement concerning the probability density function and the cumulative distribution function of a random variable?

Athe PDF is non-negative.

Bthe definite integral of the CDF from minus infinity to plus infinity is undefined.

Cthe CDF approaches 1 as its argument approaches infinity.

Dthe definite integral of the PDF from minus infinity to plus infinity is zero.

Answer : D

Question 3

Which of the following is consistent with the definition of a Type I error?

AThe probability of a Type I error is 100% minus the significance level

BA Type I error would have occurred if the performance of a stock was positively correlated with the performance of a hedge fund, but in a linear regression, the hypothesis of positive correlation was rejected

CA Type I error would have occurred if the performance of a stock was positively correlated with the performance of a hedge fund, but in a linear regression, the hypothesis of no correlation was rejected

DA Type I occurs whenever data series are serially correlated

Answer : B

Question 4

When the errors in a linear regression show signs of positive autocorrelation, which of the statements below is true?

AThe regression coefficient will be too high and the standard error of the regression coefficient will be understated

BThe regression coefficient will be too low and the standard error of the regression coefficient will be overstated

CThe regression coefficient will be unbiased, but the standard error of the regression coefficient will be understated

DThe regression coefficient will be unbiased, but the standard error of the regression coefficient will be overstated

Answer : D

Question 5

Which of the following can induce a 'multicollinearity' problem in a regression model?

AA large negative correlation between the dependent variable and one of the explanatory variables

BA high positive correlation between the dependent variable and one of the explanatory variables

CA high positive correlation between two explanatory variables

DThe omission of a relevant explanatory variable

Answer : C

Free Mathematical Foundations of Risk Measurement – 2015 Edition Questions for PRMIA Mathematical Foundations of Risk Measurement – 2015 Edition Exam as PDF & Practice Test Software

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