Point Estimates of Population Proportions

Use the sample proportion p^\hat{p} as a point estimate of an unknown population proportion pp, derive the mean and standard error of its sampling distribution, and apply the Central Limit Theorem to compute probabilities involving p^\hat{p}.

Step 1 of 119%

Tutorial

The Sample Proportion

Suppose a population contains an unknown proportion pp of individuals who have some characteristic (vote yes, are defective, support a policy, etc.). To estimate p,p, we draw a random sample of size nn and count the number XX of sampled individuals with the characteristic.

The sample proportion is

p^=Xn.\hat{p} = \dfrac{X}{n}.

We call p^\hat{p} a point estimate of pp because it produces a single numerical guess for the unknown population proportion.

For example, if a pollster surveys n=200n=200 voters and finds X=86X=86 supporters of a referendum, then the point estimate of the population proportion of supporters is

p^=86200=0.43.\hat{p} = \dfrac{86}{200} = 0.43.
navigate · Enter open · Esc close · ⌘K/Ctrl K toggle