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Discrete distributions

Build a probability distribution from a hobby

A discrete random variable takes only specific, countable values: the number of books you read in a month, for example, but never 2.5 books.

Pick a hobby. You'll build its probability distribution, then use it to find the expected value, variance, and standard deviation.

The probability distribution function (PDF)

Let X be the number of . Suppose the probability of each value is given by this function:

for x = 0, 1, 2, 3, or 4  ·  values of 5 or more have probability 0

Fill in the table. Plug each value of x into the function. Enter probabilities as decimals (10% → 0.1).

x
P(X = x)
Sum of P(X = x)
0
Using the distribution

Probability of a range of values

To find the probability that X falls in a range, add up the probabilities of the values in that range.

xP(X = x)

Expected value

What's the long-run average?

The expected value E(X) is the average you'd get over many, many repeats. Multiply each value by its probability and add the products:

E(X) = Σ x · P(X = x)
xP(X = x)

Variance · step 1 of 3

How far is each value from the mean?

Variance measures how spread out the distribution is around its expected value. We'll build it one column at a time. First, subtract the mean from each value: x − E(X), where .

xP(X = x)x − E(X)
Variance · step 2 of 3

Square each deviation

Squaring removes the negative signs, so values below and above the mean both count as spread.

xP(X = x)x − E(X)(x − E(X))²
Variance · step 3 of 3

Weight each squared deviation by its probability

Multiply each squared deviation by P(X = x). The sum of that column is the variance.

xP(X = x)x − E(X)(x − E(X))²(x − E(X))² · P(X = x)

What is the variance of X?

What is the standard deviation of X? (Round to two decimal places.)

Recap

What makes a discrete distribution