Basics to Hypothesis Testing

These flashcards cover key concepts related to hypothesis testing in statistics, including definitions of terms and their purposes within the process.

Hypothesis

An empirically testable yet unproven statement derived from the phenomenon of interest.

Null Hypothesis (H0)

A statement about a population parameter that researchers try to reject or disprove.

Alternative Hypothesis (Ha)

A statement that directly contradicts the null hypothesis and what researchers believe to be true if the null hypothesis is false.

Degrees of Freedom (df)

The number of observations that went into estimating statistical parameters; influences the critical value of hypothesis tests.

Significance Level (α)

The acceptable level of error selected by the researcher; probability of rejecting the null hypothesis when it is actually true.

p-value

A statistical measure used to determine the likelihood that an observed outcome is the result of chance.

t-test

A statistical calculation that measures the difference in means between two sample groups.

One-tailed Test

A hypothesis test that is expressed directionally, testing if a parameter is either greater than or less than a certain value.

Two-tailed Test

A hypothesis test that is without direction, testing if a parameter is different from a certain value.

Normal Distribution

A common probability distribution in statistics characterized by its symmetric bell shape and defined by mean and standard deviation.

Empirical Rule

States that for a normal distribution, almost all observed data will fall within three standard deviations of the mean.

Statistical Significance

Indicates that the results are unlikely to have occurred by chance, usually determined by the p-value comparing to the significance level.

Critical Value

The threshold against which the test statistic is compared in hypothesis testing to decide whether to reject the null hypothesis.

Sample Mean (X̄)

The average value of a sample, used in tests to evaluate hypotheses about population parameters.

Test Statistic

A standardized value calculated from sample data during a hypothesis test, used to determine whether to reject the null hypothesis.

Type I Error

The error of rejecting the null hypothesis when it is actually true.

Population Parameter

A characteristic or measure obtained by using all the data from a specific population.