Sample Questions
Question 1
Easy
Which of the following best describes a Monte Carlo simulation?
Solution
A is correct.
Monte Carlo simulation generates a large number of random scenarios based on assumed probability distributions for key input variables, producing a distribution of possible outcomes. This allows analysts to assess the range and likelihood of different results under uncertainty.
Monte Carlo simulation generates a large number of random scenarios based on assumed probability distributions for key input variables, producing a distribution of possible outcomes. This allows analysts to assess the range and likelihood of different results under uncertainty.
Question 2
Medium
In hypothesis testing, a Type I error occurs when:
Solution
B is correct.
A Type I error is the rejection of a true null hypothesis. The probability of committing a Type I error is equal to the significance level (alpha) of the test.
A Type I error is the rejection of a true null hypothesis. The probability of committing a Type I error is equal to the significance level (alpha) of the test.
Question 3
Hard
The excess kurtosis of a normal distribution is:
Solution
B is correct.
A normal distribution has a kurtosis of 3. Excess kurtosis is defined as kurtosis minus 3, so for a normal distribution, excess kurtosis = 3 - 3 = 0. A distribution with excess kurtosis greater than 0 is leptokurtic (fatter tails), while one with excess kurtosis less than 0 is platykurtic (thinner tails).
A normal distribution has a kurtosis of 3. Excess kurtosis is defined as kurtosis minus 3, so for a normal distribution, excess kurtosis = 3 - 3 = 0. A distribution with excess kurtosis greater than 0 is leptokurtic (fatter tails), while one with excess kurtosis less than 0 is platykurtic (thinner tails).
