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Psychology Exam 3
Terms & Templates
| Question | Answer |
|---|---|
| CI's for Dependent Means T-test | " -true population mean difference . . . " |
| CI's for Independent Means T-test | " -true difference between the two population means . . . " |
| Effect Size for ANOVA | " [r^2 x 100] of the variability in the outcome variable of ______ can be predicted by the predictor variable of ______." |
| P-values for Independent Means T-test | Represents the likelihood that you would have obtained a T statistic this big IF the null hypothesis of no difference between the population means was actually true. |
| P-values for Dependent Means T-test | "There is a ______% chance that I would obtain an effect this extreme IF the null hypothesis of a population mean difference score of zero was actually true. [This is unlikely, therefore I reject/likely, therefore I fail to reject.]" |
| 5 Steps of Traditional Null Hypothesis Significance Testing | 1) Restate Q as a research Q and a null hypothesis about the pops. 2) Determine characteristics of the null comp dist. 3) Determine cut-offs that are unlikely enough to be rejected. 4) Compute sample's score & map it onto null comp dist. 5) decision. |
| Pearson Correlation | - exploring associations between 2 or more numeric equal interval variables. -one predictor variable |
| Multiple Regression | exploring associations between 2 or more numeric equal interval variables. - more than one predictor variable |
| T-test (Independent Means) | - Numeric Equal Interval DV. - compares two or less means. - has diff participants and TWO means. |
| Single Sample T-test | - comparing just two or less means. - diff participants in each condition. |
| Factors that increase statistical power | - larger sample size - larger effect size -one tailed hypothesis test |
| Factorial ANOVA | - when you want to study an interaction effect to see if one IV depends on the other. |
| Statistical Significance | - tells how real an effect is. - speaks to the reality of an effect, but not the strength. |
| Effect Size | - Tells about an effect's importance or magnitude. -reflects the estimated strength of an effect. |
| Elaborated Steps of Null Hypothesis Significance Testing With Software | 1) determine nature of variables/research design 2) find+ review resources 3) run appropriate stat test/ check p-value to see if its below alpha 4) reject or fail to reject null hypothesis |
| Repeated Measures ANOVA | - comparing greater than 2 means -same participants in each condition |
| T-test (Dependent Means) | - Numeric equal interval DV - compares 2 or less means - has same participants |
| One-Way ANOVA | - numeric equal interval DV - compares greater than 2 means - diff participants in each sample |
| F-ratio Distribution | The null comparison distribution for the ANOVA that reflects the distribution of F-ratios, IF the null hypothesis of no population mean difference was true. |
| F-ratios in the middle region | - are likely to be obtained IF the null hypothesis is true (fail to reject the null) |
| F-ratios in the outside region | - are unlikely to be obtained IF the null is true (fail to reject the null) |
| t score for independent means T-test formula | t = (sample mean - population mean) / Estimated SD |
| t score for dependent means T-test formula | t = (sample mean 1 - sample mean 2) / S-difference |
| F-ratio for an ANOVA formula | F = S^2-between / S^2-within = 5 |
Created by:
feartoconquer
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