Sampling Distribution
The name for the distribution of a statistic from all possible samples of the same size.
Sampling distribution
The condition checked using np ≥ 10 and n(1–p) ≥ 10.
Large Counts
The theorem that says x‑bar becomes normal as n increases.
Central Limit Theorem
A sampling method that systematically favors certain outcomes.
Biased sample
A number that describes a population.
Parameter
The term for natural differences between samples.
Sampling variability
The mean of the sampling distribution of p‑hat.
p
The mean of the sampling distribution of x‑bar.
μ
Increasing sample size reduces this.
Variability
A number that describes a sample.
Statistic
The center of a sampling distribution of a statistic.
The parameter
The standard error of p‑hat.
√[p(1–p)/n]
The standard error of x‑bar.
σ / √n
A graph with high spread but centered correctly shows high what?
Variability
The term for the SD of a statistic’s sampling distribution.
Standard error
What happens to spread when sample size increases.
Spread decreases
The condition that ensures independence when sampling without replacement.
10% condition
The minimum sample size often used for CLT when population is skewed.
n ≥ 30
A graph centered incorrectly shows high what?
Bias
The symbol for population proportion.
p
The formula for standard error of a sample mean.
σ / √n
The shape of p‑hat’s distribution when conditions are met.
Approximately normal
The shape of x‑bar’s distribution if the population is normal.
Normal for any n
The best way to reduce bias.
Random sampling
The symbol for sample mean.
x‑bar