Chapter 5 Sampling Distributions Flashcards

Vocabulary flashcards for reviewing sampling distributions concepts.

Parameter

A number that describes a characteristic of the population.

Statistic

A number that describes a characteristic of a sample.

Sampling Variability

The value of a statistic varies in repeated random sampling.

Sampling Distribution

The distribution of values taken by the statistic in all possible samples of the same size from the same population.

Bias

Concerns the center of the sampling distribution; an unbiased statistic has a mean of its sampling distribution equal to the true parameter value.

Variability

The spread of the sampling distribution; smaller for larger samples.

Population Distribution

The distribution of values of the variable among all individuals in the population.

Central Limit Theorem

As sample size increases, the distribution of sample means becomes approximately Normal, regardless of the population distribution shape.

Binomial Setting (BINS)

Conditions for a binomial setting: Binary (success/failure), Independent trials, Number of trials fixed, Same probability of success.

Binomial Distribution

The probability distribution of the count X of successes in a binomial setting. X~B(n,p)

Normal Approximation for Binomial Distributions

When n is large (np ≥ 10 and n(1 – p) ≥ 10), the binomial distribution of X is approximately Normal with mean np and standard deviation sqrt(np(1-p)).

Sample Proportion

The count of successes in the sample divided by the sample size: 𝑝𝑝̂ = X/n

Sampling Distribution of a Sample Proportion

For large n, 𝑝𝑝̂ has approximately a Normal distribution with mean p and standard deviation sqrt(p(1-p)/n).