Term
|
Definition
|
|
Term
Chi-Squared Assumptions
(3) |
|
Definition
1. Variables are categorical (discrete)
2. Independence of observations
3. Normality |
|
|
Term
| Chi-Squared Effect Size and df |
|
Definition
Φ (Phi) for 2x2
Cramer's V otherwise
Χ2 (df, N = ?) = ? |
|
|
Term
Chi-Squared APA format requirments
(3) |
|
Definition
1. Description of variables
2. Results of test
3. Interpretation of results |
|
|
Term
|
Definition
Click Data -> Select Cases
Click If condition is satisfied
Click “If”
Type in (present = 1 or present = 2) and (rating = 1 or rating = 3)
Click Continue
Click OK.
Click Analyze -> Descriptive Statistics -> Crosstabs.
Everything should be ready to go. Click OK. |
|
|
Term
Correlation Assumptions
(2) |
|
Definition
1. Homogeneity of variances
2. Normality of X and Y of variance in arrays |
|
|
Term
| Correlation - Effect Size and DF |
|
Definition
r2 = % of variance accounted for by relationship
r(df) N-2 = ? |
|
|
Term
| Correlation APA write-up requirements |
|
Definition
1. Description of correlated variables
2. Significant correlation coefficients
3. Interpretation of findings
4. Scatterplot matrix |
|
|
Term
Factorial ANOVA assumptions
(4) |
|
Definition
1. Normality
2. Independence between subjects
3. Sphericity
4. One DV, 2 or more IVs |
|
|
Term
| Factorial ANOVA effect size and DF |
|
Definition
| partial η2 F(df, error df) = ? |
|
|
Term
Factorial ANOVA APA write up
(4) |
|
Definition
1. Description of the data (i.e., IV conditions, outcome measure)
2. Purpose of the test (e.g., evaluate relationship)
3. Description of participants
4. Results of omnibus test and effect size |
|
|
Term
|
Definition
|
|
Term
Independent Sample t-test
(4) |
|
Definition
1. Data is continuous (interval or ratio)
2. Homogeneity of variances
3. Normality of the distribution of differences between sample means (for matched pairs and independent groups)
4. Population variance is unknown and normal |
|
|
Term
| Independent t-test effect size and DF |
|
Definition
d = (x1-x2)/mean SD
t(df) = ? |
|
|
Term
| Independent t-test APA write up |
|
Definition
1. Description of data
2. Purpose of analysis (differences)
3. Descriptives (M, SD)
4. Results of test and interpretation |
|
|
Term
1-sample t-test assumptions
(3) |
|
Definition
1. Data is continuous (interval or ratio)
2. Homogeneity of variances
3. Population variance is unknown and normal |
|
|
Term
One sample t-test APA write up
(4) |
|
Definition
1. Description of data
2. Purpose of analysis
3. Descriptives (M, SD)
4. Results of test and interpretation |
|
|
Term
One-way ANOVA assumptions
(5) |
|
Definition
1. 1 predictor (multiple conditions), 1 outcome
2. Homogeneity of variance
3. Normality
4. Independence of observations (like x2)
5. Same N for every group |
|
|
Term
| One-way ANOVA effect size and DF |
|
Definition
η2 or ω2
F(df, error df) = ? |
|
|
Term
| One-way ANOVA APA write up |
|
Definition
1. Description of the data (i.e., IV conditions, outcome measure)
2. Purpose of the test (e.g., evaluate relationship)
3. Description of participants
4. Results of omnibus test and effect size |
|
|
Term
|
Definition
|
|
Term
Paired-sample t-test assumptions
(4) |
|
Definition
1. Data is continuous (interval or ratio)
2. Homogeneity of variances
3. Normality of the distribution of differences between sample means (for matched pairs and independent groups)
4. Population variance is unknown and normal |
|
|
Term
Paired sample t-test APA writeup
(4) |
|
Definition
1. Description of data
2. Purpose of analysis (differences)
3. Descriptives (M, SD)
4. Results of test and interpretation |
|
|
Term
Regression Assumptions
(4) |
|
Definition
1. Linearity (i.e., as X increases Y either increases or decreases, so there is a dependent relationship)
2. Homogeneity of variance in arrays
3. Normality of y, given the normality of x
4. Y is continuous, but X is not (usually) |
|
|
Term
|
Definition
| r2 = % of variance accounted for by relationship |
|
|
Term
Regression APA writeup
(4) |
|
Definition
1. Purpose of regression analysis
2. Regression equation: Ŷ = bx + a
3. Relevant correlation coefficient and associated t-test
4. Effect size (% of variance accounted for by linear relationship |
|
|
Term
Repeated Measures ANOVA Assumptions
(3) |
|
Definition
1. Normality
2. Sphericity (if not met, adjust analysis with Greenhouse-Geisser)
3. Independence between subjects |
|
|
Term
| Repeated Measures ANOVA effect size and DF |
|
Definition
Partial η2
F(df, error df) = ? |
|
|
Term
Repeated Measures ANOVA APA writeup
(4) |
|
Definition
1. Description of the data (i.e., conditions, outcome measure)
2. Purpose of the test (e.g., evaluate relationship)
3. Description of participants
4. Results of omnibus test and effect size |
|
|
Term
Repeated Measures Post-Hoc Test
(2) |
|
Definition
Polynomial contrast (when variable is continuous); Tukey's LSD
partial η2 |
|
|
Term
Nonparametric Tests Assumption
(4) |
|
Definition
1. Groups resemble each other
2. Sample resembles population
3. Smaller sample size
4. Unclear assumption fit |
|
|
Term
| Nonparametric Tests effect size and DF |
|
Definition
η2 or Kendall's W
Χ2 (df, N = ?) = ? or z (df) = ? |
|
|
Term
Nonparametric tests APA Write ups
(4) |
|
Definition
1. Description of the data (i.e., conditions, outcome measure, N, Medians)
2. Purpose of the test
3. Type of analysis conducted
4. Results of omnibus test |
|
|
Term
|
Definition
| Nonparametric independent groups or nonparametric 2 related samples |
|
|
