CHEAT SHEET FOR UNIT 3: NULL HYPOTHESIS SIGNIFICANCE TESTING

These flashcards cover essential terms and concepts related to Null Hypothesis Significance Testing, helping students prepare for exams.

Null Hypothesis Significance Testing (NHST)

A testing method that helps simplify complex problems by making an assumption about part of the problem and collecting data to check for inconsistencies with that assumption.

Null Hypothesis (H0)

The hypothesis that assumes there is no effect or no difference; it is what we seek to falsify in NHST.

Alternative Hypothesis (HA)

The hypothesis that contradicts the null hypothesis; it is considered if data is found to be inconsistent with H0.

Test Statistic

A score used to indicate how inconsistent the observed data are with the null hypothesis.

P Value

The probability of observing a test statistic as extreme as the observed one, given that the null hypothesis is true.

Statistically Significant

A term describing results where the p value is less than a predetermined threshold (commonly 0.05), leading to rejection of the null hypothesis.

Practical Significance

The consideration of whether the results of a test have real-world relevance or importance, beyond purely statistical significance.

Type of Tests

Different NHST types include one-sample tests (comparing one group) and two-sample tests (comparing two groups).

Independent Samples

Samples in NHST where different subjects are used in each comparison group.

Paired Samples

Samples in NHST where the same subjects are measured under different conditions.

One-Sided Test

A test that specifies the alternative hypothesis as being either greater than or less than the null hypothesis.

Two-Sided Test

A test that considers the alternative hypothesis as being different from the null hypothesis, without specifying direction.

T-Test

A statistical test used for comparing the means of numeric/continuous variables.

Degrees of Freedom (df)

A parameter that reflects the number of values in a statistical calculation that are free to vary, impacting the distribution of test statistics.

F-Test

A test used to compare the means of numeric/continuous variables across categories of a categorical variable, primarily used in ANOVA.

Chi-Squared Test (χ2-Test)

A statistical test used for comparing observed frequencies of discrete data against expected frequencies.

Frequency Distribution

A representation of the number/proportion of data points in each category of a variable.

Contingency Table

A table used to display the frequency distribution of categorical variables.