# Quiz 1: Discrete Distributions

Test your knowledge of the material on discrete distributions in the following quiz.

1. What are the assumptions necessary for a variable to be distributed as a binomial distribution?
1. The variable must be binary
2. The variable must be discrete
3. The variable must have a fixed number of trials
4. All of the above
1. How does the skewness of a binomial variable relate to its parameters n and p?
1. Skewness = n p
2. Skewness = n/p
3. Skewness = p (1-p) / n
4. Skewness = p^2 / n
1. When would you use a negative binomial distribution over a Poisson distribution?
1. When the number of trials is fixed
2. When the variance exceeds the mean
3. When there are negative counts in the data
4. When the parameter p differs substantially from 0.5
1. How does the mean and variance of a Poisson distribution relate to its parameter λ?
1. Mean = λ, Variance = λ
2. Mean = 1/λ, Variance = 1/λ^2
3. Mean = 1/λ, Variance = λ
4. Mean = λ, Variance = λ^2
1. Which example is most likely to follow a log-series distribution?
1. Number of accidents at a busy intersection
2. Counts of occurrences of distinct words in the books written by Jane Austin
3. Number of births of males in Canadian families composed of 6 children
4. Number of tosses of a coin required to get the first head.
1. **Which of the following characterize the negative binomial distribution and the geometric distribution?
1. The negative binomial distribution models the number of failures before a specified number of successes
2. The geometric distribution models the number of failures before the first success
3. Both A and B
4. Neither A nor B
1. In what type of data might you use a negative binomial distribution?
1. Count data
2. Binary data
3. Continuous data
4. Both A and B
1. What is the mean and variance of a variable distributed as a geometric distribution?
1. Mean = λ, Variance = λ
2. Mean = 1/λ, Variance = 1/λ^2
3. Mean = 1/λ, Variance = λ
4. Mean = λ, Variance = 1/λ^2