Hypotheses and Statistical Errors

These flashcards cover the key concepts related to hypotheses in statistics, including definitions of null and alternate hypotheses, types of errors, and the relationship between hypotheses.

Null Hypothesis (H0)

The assumption that there is no effect or no difference; any observed effect is due to chance.

Alternate Hypothesis (HA or H1)

The hypothesis that suggests there is an effect or a difference; the observed effect is not due to chance.

Directional Hypothesis

A hypothesis that specifies the direction of the expected effect; also known as one-tailed.

Non-Directional Hypothesis

A hypothesis that does not specify a direction of the effect; also known as two-tailed.

Type I Error

Rejecting the null hypothesis when it is actually true; a false positive.

Type II Error

Retaining the null hypothesis when it is actually false; a false negative.

Mutually Exclusive Hypotheses

Two hypotheses that cannot both be true at the same time.

Exhaustive Hypotheses

Hypotheses that cover all possible outcomes of an experiment.

True State of Affairs

The actual state regarding the null hypothesis, which is either true or false.

False Positive

Believing there is an effect when there is none, typically related to a Type I error.

False Negative

Believing there is no effect when there actually is one, typically related to a Type II error.