Statistical Tests Flashcards
Single Sample Chi-Square Test
Used to analyze NOMINAL data from a descriptive study that includes only ONE variable
Multiple Sample Chi-Square Test
Used to analyze NOMINAL data from…
(a) a descriptive study that has 2 or more variables that can’t be identified as independent or dependent variables, OR
(b) an experimental study that has independent and dependent variables.
Student’s T-Test (General)
Used when:
- a study includes 1 CATEGORICAL independent variable that has “exactly” 2 levels, AND
- 1 CONTINUOUS dependent variable (i.e., measured on an interval or ratio scale).
Note: I say “exactly” 2 levels because separate t-tests could be run to simulate a One-way ANOVA but this would increase experimentwise/familywise error rate.
T-test for a single sample
Used to compare an obtained sample mean to a known population mean.
T-Tests for unrelated (uncorrelated) samples
Used to compare the means obtained by 2 groups when subjects in the groups are unrelated (e.g., when subjects were randomly assigned to one of the two groups).
T-test for related (correlated) samples
Used to compare the means obtained by 2 groups when there’s a relationship between subjects in the two groups. This occurs when:
(a) participants are “natural” pairs (e.g., twins), and members of each pair are assigned to different groups;
(b) participants are matched in pairs on the basis of their pretest scores or status on an extraneous variable, and members of each pair are assigned to different groups; or
(c) a single-group pretest-posttest design is used and subjects are “paired” with themselves.
One-way ANOVA
Used when a study includes:
- 1 CATEGORICAL independent variable that has MORE THAN 2 levels, AND
- 1 dependent variable that’s measured on a CONTINUOUS scale (i.e., an interval or ratio scale) and the groups are unrelated.
It produces an F-ratio. Numerator is “mean square between” (MSB). Denominator is “mean square within” (MSW). Whenever the F-ratio is larger than 1.0, this suggests that the independent variable has had an effect on the dependent variable.
Factorial ANOVA (i.e., two-way, three-way, four-way, etc. ANOVA)
Used when a study includes MORE THAN 1 independent variable.
Mixed (Split-Plot) ANOVA
Used when the data were obtained from a study that used a mixed design – i.e., when the study included at least one between-subjects independent variable and at least one within-subjects independent variable.
A classic example of a split-plot ANOVA study would be an agricultural experiment where different fertilizer types (considered the “whole plot” factor) are applied to large plots of land, and then within each plot, different plant varieties (the “split-plot” factor) are randomly assigned to smaller subplots, with the researchers measuring the yield of each variety under each fertilizer treatment; this allows them to analyze the effects of both fertilizer type and plant variety while accounting for the variability between large plots of land.
Randomized block ANOVA
Used to control the effects of an extraneous variable on a dependent variable by including it as an independent variable and determining its main and interaction effects on the dependent variable.
When using the randomized block ANOVA, the extraneous variable is referred as the “blocking variable.”
Analysis of Covariance (ANCOVA)
Used to control the effects of an extraneous variable on a dependent variable but does so by statistically removing its effects from the dependent variable.
When using the ANCOVA, the extraneous variable is the “covariate.”
Multivariate analysis of variance (MANOVA)
Used when a study includes 1 OR MORE independent variables and 2 OR MORE dependent variables that are each measured on an interval or ratio scale.
Trend Analysis
Used when a study includes one or more quantitative independent variables and the researcher wants to determine if there’s a significant linear or nonlinear (quartic, cubic, or quadratic) relationship between the independent and dependent variables.
Post-Hoc Tests
Conducted when an ANOVA produces a significant F ratio. Frequently used post hoc tests include Tukey’s honestly significant difference (HSD) test, the Scheffe test, and the Newman-Keuls test.
Multiple Regression
When 2 OR MORE predictors will be used to estimate status on ONE criterion that’s measured on a CONTINUOUS scale.
Simultaneous (standard) multiple regression involves entering data on all predictors into the equation simultaneously.
Stepwise multiple regression involves adding or subtracting one predictor at a time to the equation in order to identify the fewest number of predictors that are needed to make accurate predictions.
