16 terms

Statistic

A quantity computed from the values in a sample; denoted using Latin letters and used to estimate population parameters

Sampling Distribution

Provides the LONG-RUN behavior of a sample statistic when sample after sample is selected; shows the value of the statistic for EVERY possible different sample of a given size from a population.

Sample proportion

Fraction of individuals or objects in a sample that have some characteristic(s) of interest.

Sampling Distribution of a Sample Proportion

Provides the LONG-RUN behavior of the sample proportion that is necessary for making inferences about a population proportion.

Sampling variability

Variation that is observed from sample to sample and occurs because the observed value of a statistic depends on that particular sample; can be reduced by increasing sample size

Central Limit Theorem

When the sample size (n) is sufficiently large, the distribution of sample means is approximately normal regardless of the shape of the population distribution

Low p values

Result in positively skewed distributions. The exact opposite results in negatively skewed distributions.

Sampling Distribution of a Sample Mean

Provides the LONG-RUN behavior of the sample mean that is necessary for making inferences about a population mean.

Mean of sampling distribution of the sample mean

Always equals the population mean regardless of sample size

Mean of sampling distribution of the sample proportion

Always equals the population proportion regardless of sample size

Standard deviation of the sampling distribution of the sample mean

Always gives the typical difference between an individual sample mean and the true (population) mean regardless of sample size

Standard deviation of the sampling distribution of the sample proportion

Always gives the typical difference between an individual sample mean and the true (population) mean regardless of sample size

n(p) > 10 AND n(1 - p) > 10

Ensures that the sampling distribution of the sample proportion is approximately normal

Population Distribution is Normal OR n > 30

Ensures that the sampling distribution of the sample mean is approximately normal

10% condition

Ensures that the selection of individuals for a sample remains practically independent, even when sampling without replacement;

Graph of sample distribution

Used to check for skew or outliers in the sample data that might suggest that the population distribution is not normally distributed; only used when testing for means, n is not large enough to invoke CLT and no information is given on the population distribution's shape