7 terms

Fundamentals of Statistics, 3rd ed - Sullivan

sampling distribution

a probability distribution for all possible values of the statistic as computed from a sample of size n

sampling distribution of the sample mean

the probability distribution of all possible values of the random variable x̄ computed from a sample size n from a population with mean µ and standard deviation σ

standard error of the mean

the standard deviation of the sampling distribution of x̄; σ-sub-x̄ = σ/√n

central limit theorem

regardless of the shape of the underlying population, the sampling distribution of x̄ becomes approximately normal as the sample size, n, increases

sample proportion

p̂ = x/n where x is the number of individuals in the sample with the specified characteristic. The sample proportion, p̂, is a statistic that estimates the population proportion, p.

p̂

sample proportion

sampling distribution of p̂

For a simple random sample of size n with a population proportion p,

1. The shape of the sampling distribution of p̂ is approximately normal provided np(1 - p) ≥ 10

2. The mean of the sampling distribution of p̂ is µ-sub-p = p

3. The standard deviation of the sampling distribution of p̂ is

σ-sub-p = √[(p(1 - p))/n]

1. The shape of the sampling distribution of p̂ is approximately normal provided np(1 - p) ≥ 10

2. The mean of the sampling distribution of p̂ is µ-sub-p = p

3. The standard deviation of the sampling distribution of p̂ is

σ-sub-p = √[(p(1 - p))/n]