1. A probability experiment which outputs a single number is a(n) _______________ ________________.
(two words)
2. A discrete random variable can output either a finite or a(n) ______________(countably, uncountably)
infinite number of values.
3. A continuous random variable has its values in one or more __________________. An example is the __________________ distribution whose density function is the horizontal line from X=a to X=b.
4. The _________________ __________________ (two words) of a discrete random variable lists every possible value that the variable can assume and the corresponding probabilities.
5. For a(n) _________________ random variable, a sample is drawn with replacement, or there is a large population size. Successive trials are independent of each other. There is a categorical variable with 2 possible values. The ________________(population, sample) is of a fixed size n.
6. For a ____________________ random variable, a sample is drawn without replacement. Successive trials are dependent on each other. There is a ____________________ (population, sample) of finite size N and a categorical variable with 2 possible values. The sample is of a fixed size _______ (N, n, p, q, r).
7. For each blank, include both the formula and the exact answer; do not use a calculator.
Given a uniform distribution with the sample space [1, 4], the height of its density function is ________________ and it has mean ________________ and standard deviation __________________.
8. The ___________________ ____________________ (two words) distribution has a density function that is bell shaped and symmetric. Its mean is 0 and its standard deviation is 1.
9. The ___________________ is also known as the average, expectation and expected value.
10. The ___________________of a discrete random variable can be found by taking the product of each outcome and its probability and then summing.
11. The ______________________ (one word!) of a discrete random variable can be found by subtracting the square of its mean from the expectation of the square of the random variable.