ap stats -- unit 5

sampling distribution

sampling distribution

shows the statistic found for all possible samples of size n

sampling variability

increase n, decrease variability

categorical data gives

proportions (p hat)

quantitative data gives

sample means (x bar)

proportions

p^

proportion conditions

randomization

independence

10% condition

~Normal

Large Enough Condition

if we can expect at least 10 successes and failures then the sampling distribution of p^ is ~Normal

Central Limit Theorem (CLT)

in a skewed population, increasing the n makes the distribution closer to ~Normal

n≥30 is sufficient to apply CLT

conditions for sample means (x bar)

~Normal - population distribution is ~N or n≥30 and CLT applies

randomization

independence (10% condition)