Inferences about Means

Vocabulary flashcards related to inferences about means, covering concepts like t-distribution, standard error, margin of error, Student's t-model, confidence intervals, assumptions, and Central Limit Theorem.

T Distribution

A sampling distribution model used for means when the population standard deviation is unknown and estimated from the sample.

Standard Error

An estimate of the standard deviation of a sampling distribution.

Margin of Error

The extent of the interval on either side of the sample statistic in a confidence interval.

Student’s t-model

A family of distributions indexed by degrees of freedom, used when estimating the mean of a population when the sample size is small and the population standard deviation is unknown.

Degrees of Freedom (df)

A parameter that affects the shape of the t-distribution; typically n-1 for single sample designs.

Confidence Interval

An interval estimate for a population parameter, calculated with a given confidence level.

Randomization Condition

The data arise from a random sample or suitably randomized experiment.

10% Condition

When sampling without replacement, the sample size should be no more than 10% of the population.

Nearly Normal Condition

The data should follow a normal model reasonably closely; check with a histogram.

Central Limit Theorem (CLT)

The sampling distribution of the sample mean approaches a normal distribution as the sample size increases, regardless of the shape of the population distribution.

One-Sample t-Interval for the Mean

A confidence interval for the population mean based on a sample; used when the population standard deviation is unknown.