Confidence Intervals and Hypothesis Testing

These flashcards cover key concepts related to Confidence Intervals and Hypothesis Testing, as discussed in the lecture notes.

Confidence Interval (CI)

A statistical range that is likely to contain the true population parameter, calculated from sample data.

Margin of Error (MoE)

The largest likely sampling error in a sample statistic, often expressed as a percentage.

t Distribution

A probability distribution used to estimate population parameters when the sample size is small and the population standard deviation is unknown.

Null Hypothesis (H0)

A statement suggesting that there is no effect or difference, and any observed effect is due to sampling error.

Alternative Hypothesis (H1)

A statement indicating the presence of an effect or a difference in the population, suggesting that the observed effect is real.

Degrees of Freedom (df)

The number of independent values or quantities that can vary in a statistical analysis, typically calculated as sample size minus one.

p-value

The probability of obtaining a test statistic at least as extreme as the one observed, assuming the null hypothesis is true.

Standard Error (SE)

An estimate of the variability of a sample statistic, calculated as the sample standard deviation divided by the square root of the sample size.

Sampling Error

The difference between a sample statistic and the corresponding population parameter it estimates.

α (Alpha Level)

The threshold for determining statistical significance; commonly set at 0.05, representing a 5% risk of concluding that a difference exists when there is none.

Hypothesis Testing

A statistical method used to decide whether to reject the null hypothesis based on sample data.

Statistical Hypotheses

Statements that specify the expected relationship or differences in a population, against which data are tested.

Test Statistic

A standardized value that is calculated from sample data during a hypothesis test, used to evaluate the null hypothesis.