MM107 Hypothesis Testing - 2 Sample t-Test

These flashcards cover key vocabulary related to hypothesis testing and the two-sample t-test, suitable for exam preparation.

Hypothesis Testing

A statistical method for testing a claim about a population based on sample data.

Null Hypothesis (H0)

The hypothesis that there is no effect or difference, and it is typically what we test against.

Alternative Hypothesis (H1)

The hypothesis that there is an effect or difference, and it is what we aim to provide evidence for.

Mean Difference

The difference between the means of two groups that is being tested in hypothesis testing.

p-value

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

Significance Level (α)

The threshold at which we decide whether to reject the null hypothesis, commonly set at 0.05.

Two-Tailed Test

A hypothesis test that evaluates if a parameter is either greater than or less than a certain value.

One-Tailed Test

A hypothesis test that evaluates if a parameter is greater than or less than a certain value, but not both.

Degrees of Freedom (df)

The number of independent values or quantities which can be assigned to a statistical distribution.

Effect Size

A quantitative measure of the magnitude of a phenomenon; indicates the size of the difference between groups.

Test Statistic

A standardized value that is calculated from sample data during a hypothesis test.

Confidence Interval

A range of values derived from sample statistics that is likely to contain the value of an unknown population parameter.

Variance

A measure of how far a set of numbers are spread out from their average value.

T-test

A statistical test used to determine if there is a significant difference between the means of two groups.

Z-test

A statistical test used to determine if two population means are different when the variances are known.