Nonparametric Tests in PSYC 2101

These flashcards cover key concepts and terminology related to Nonparametric Tests as outlined in the PSYC 2101 course materials.

Nonparametric Tests

Statistical tests not requiring data to fit a normal distribution.

Distribution Free Statistics

Another term for nonparametric tests, implying fewer data assumptions.

Goodness of Fit

Chi-square test assessing if observed frequencies match expected frequencies.

How to Conduct Goodness of Fit Test

Compare observed frequencies of a single categorical variable to expected frequencies.

Independence Test

Chi-square test for significant association between two categorical variables.

How to Conduct Independence Test

Examine the association between two categorical variables using a contingency table.

When to Use Chi-Square Tests

For research designs involving categorical data to test goodness of fit or independence.

Chi-Square Statistic

Test statistic comparing expectations to observed data.

Cohen’s w

Effect size measure for chi-square tests, showing association strength.

Phi-Coefficient

Association measure for two binary variables in chi-square tests.

Cramer’s V

Association measure for nominal data, showing strength between two variables.

Hypothesis Testing

Method for testing population assumptions/claims using sample data.

α (Alpha Level)

Statistical significance threshold, often set at 0.05.

Sample

A subset of the population used for statistical analysis.

Categorical Data

Data categorized into distinct groups.

Rank Data

Data ordered or ranked, not measured at standard intervals.

Random Sample

Sample where every individual has an equal chance of selection.

Marketing Study

Research to determine consumer preferences and behavior.

Taste Test

Experiment where participants evaluate products based on flavor.

Contingency Table

Table displaying frequency distribution of variables, often in chi-square tests.

Self-Evaluation

Assessment of one's understanding and learning objective accomplishment.

Statistical Techniques

Methods to analyze and interpret quantitative data.

Population Parameters

Characteristics or measures of an entire population assessed by statistical tests.

Research Design

Overall strategy or plan for conducting research and analyzing data.