82 - D | FINAL EXAM CHEAT SHEET | PSYU4418 (Design & Statistics IV)

Description

PSYU4418 (Design & Statistics IV) - FINAL EXAM CHEAT SHEET PSYCHOLOGY HONOURS STUDENTS - This cheat sheet is organised and categorised into all relevant information corresponding to each statistical analysis covered in this unit. IMPORTANT NOTE: The weeks/topics are split up into coloured headings (, each week corresponding to a different topic/analysis). Important terms are bolded and underlined BUT they are also COLOURED CODED ACCORDING TO THEIR CATEGORIES; for example, EQUATIONS are BLUE, IMPORTANT TERMS/DEFINITIONS are RED, and so on. **THEREFORE, PLEASE PRINT THIS OUT IN COLOUR - IT WILL HELP WITH SEARCHING QUICKLY DURING YOUR EXAM AND YOU WILL SAVE TIME!** I also received an HD on the written component of this unit. This cheat sheet will come in handy for the mid-session quiz, final exam, and your thesis. Good luck this year. This unit is challenging however YOU CAN DO IT, as long as you do your best to revise the content each week. Having this cheat sheet will save you time writing your own towards the end of the semester. This took me a few weeks to put together! Information on this cheat sheet (in a nutshell) includes: - FORMULAS/EQUATIONS - STATA COMMANDS - ASSUMPTION TESTING - DEFINITIONS - PURPOSE OF ANALYSIS AND EACH OF ITS ASSOCIATED COMPONENTS - **** & MORE **** WEEKS 1 - 13 FOUNDATIONAL BACKGROUND INFO: 3RD YEAR EQUATIONS, , > Root MSE > Residual SD > Conditional Variance CI > t, b, SE > SSE > R-squared > 95% CI > Standardised Residuals MISCELLANEOUS NOTES, , > General vs. Generalized Linear Model > Johnson-Neyman Region of Significance > Equations > Stata Commands - Reverse Coding - Categorical Cut-Offs - Cat x Num IV on N DV Simple Effects POWER: > Power Table (, Type I and II Error) > Power Functions > Power Functions in Stata (Commands) LOGISTIC REGRESSION > Purpose/Method > Model Fit > Probability & Frequency Calculations > Equations > Dichotomous Logistic Regression > Ordinal Logistic Regression > Multinomial (Nominal) Logistic Regression > Stata Commands (how to run & purpose of commands) - Ordinal Logistic Regression - Multinomial Logistic Regression > Interpreting Results MANOVA > Purpose/Method > Definitions of terms & tests (, Latent Discriminant Function, Eigenvalue, Eigenvector) > Hypothesis Testing (, Wilk's Lambda, Pillai's Trace, Roy's Largest Root, Lawley-Hotelling Trace) > Interpretation of Results > Assumptions (what each assumption test is responsible for) > Assumption Testing in Stata (with commands & explanations) > How to Run MANOVA in Stata (commands in order & purpose of commands) MULTI-LEVEL MODELLING (MLM) > Purpose/Method > MLM Terms and Definitions > MLM Effects > Equations (, repeated measures designs, Level 1 & 2, Nested, Intraclass Correlation) > MLM Model Types > Effect Sizes > Model Comparison > Longitudinal Data > Covariance Structures > Grand vs. Group Mean Centring > MLM Assumptions > How to Run MLM in Stata (in order, what each command tests for) PATH ANALYSIS (PA) VIA REGRESSION > Purpose/Method > Effects (, direct, indirect, total, spurious, correlation effects) > Significance of Effects > Stata Commands (how to run each effect and interpretation) PATH ANALYSIS (PA) VIA STRUCTURAL EQUATION MODELLING (SEM) > Variable Types > Parameters and Identification (incl. equations) > Goodness of Fit (GoF) > Equations > GoF Model Comparison > Assumptions > How to Run in Stata (with commands, explanations, and interpretation) EXPLORATORY FACTOR ANALYSIS (EFA) > Important Terms (, missing data, Kaiser's criterion, total variance) > Obtaining Scores > Model Fit > Types of Variances > PAF vs. PCA > Types of Rotation (, orthogonal, oblique) > Potential Issues with EFA > Assumptions > Stata Commands (in order, how to run EFA, explanation and interpretation) PRINCIPAL COMPONENTS ANALYSIS (PCA) > Purpose/Method > Variable Definitions > Component Scores & Weights > Variable Scores & Loadings > Equations > Stata Commands (How to Run PCA) PRINCIPAL AXIS FACTORING (PAF) > Purpose/Method > Latent Variables > Factor & Variable Scores, Weights, & Loadings > PAF vs. Other Methods > Equations > Running PAF in Stata CONFIRMATORY FACTOR ANALYSIS (CFA) > Samples > Constraints > Loadings > Modification Indices (MI) > Reliability > Model Fit > Stata Commands