–ניתוחי רגרסיהSPSS ניתוחים מתקדמים ב תוכן הקורס 1. Introduction to regression A simple regression analysis Fitting lines to data Goodness-of fit How a line is fit Residual and influential points What does linear model mean? Assumption of the general linear model 2. Examining the data Univariate exploration – independent variables Measures of central tendency Variability measures Shape of the distribution Univariate exploration – dependent variables Relations with the dependent variable 3. Simple regression: Fit and Assumption Running simple regression Information about residuals Assumption of the analysis 4. Multiple Regression: Fit and Assumption Running multiple regression Regression results Residual analysis Diagnostic plots The need of a substantive model of causation 5. Stepwise regression Methods of selection Evaluating fit Running stepwise regression Stepwise output Statistical significance and practical importance Over fitting 6. Influential points and multicollinearity Influential points Multicollinearity Requesting the diagnostic Regression output Influence measures Using explore to locate extremes What to do about unusual points Effects of large samples What if a cluster of points is unusual Revisiting multicollinearity 7. Dummy variables Dummy variable coding A simple example Error distribution Using variables with more than to categories Dummy variables and missing data Regression with a three-category dummy variable Using two categorical variables Regression with continuous and dummy variables Appendix: Other dummy variable coding schemes 8. Logistic regression Introduction to logistic regression A first example of logistic regression Stepwise logistic regression ROC curves 9. Multinomial logistic regression Multinomial logistic model A multinomial logistic analysis: Predicting credit risk Appendix: multinomial logistic with a two-category outcome www.genius.co.il 03 -9222204 49170 פתח תקוה7796 .ד. קרית מטלון ת, 7 הסיבים בישראלSPSS נציגת,ג'ניוס מערכות בע"מ 10. Modeling interactions Defining interactions Interactions of dummy variables Adding a continuous variable Graphing interactions Interactions between categorical and continuous variables Centering interval variables Adding additional variables 11. Polynomial regression Curvilinear regression Fitting a quadratic model with the Curve estimation procedure Polynomial regression using the linear regression procedure Further advice on polynomial models 12. Non linear regression What does nonlinear mean Assumption of nonlinear regression An example: Oxygen concentration over time Extensions: Constrained nonlinear regression www.genius.co.il 03 -9222204 49170 פתח תקוה7796 .ד. קרית מטלון ת, 7 הסיבים בישראלSPSS נציגת,ג'ניוס מערכות בע"מ –ניתוחי שונותSPSS ניתוחים מתקדמים ב תוכן הקורס 1. Introduction to ANOVA Why do analysis of variance Visualizing analysis of variance What is analysis of variance Variance of means A formal statement of ANOVA assumptions 2. Examining data and testing assumptions Exploratory data analysis Measures of central tendency Variability measures A look at the groups Effects of violations of assumptions in ANOVA 3. One factor ANOVA Logic of testing for means differences Running one-factor ANOVA One-factor ANOVA results Post-Hoc testing Planned comparisons One-factor nonparametric analysis 4. Multi-Way univariate ANOVA Introduction to multi-way ANOVA Logic of testing and assumptions Interactions Exploring the data Two-factor ANOVA Post Hoc and simple effect test Unequal samples and unbalanced designs 5. Multivariate analysis of variance Introduction to MANOVA MANOVA assumptions Example: memory influences 6. Within-Subject design: repeated measures Introduction to repeated measures analysis One factor repeated measures analysis example Planned comparison 7. Between and within subjects ANOVA A split-plot example Split-plot analysis Appendix: Ad viewing with Pre-Post brand ratings 8. Mixed models ANOVA Mixed models with complex covariance structures Data organization for linear mixed models Linear mixed models analysis Mixed models with alternative covariance structures 9. Analysis of covariance Introduction to ANCOVA ANCOVA analysis Repeated measures ANCOVA with a single covariate s 10. Special topics Latin square designs Random effects models Hierarchical linear models www.genius.co.il 03 -9222204 49170 פתח תקוה7796 .ד. קרית מטלון ת, 7 הסיבים בישראלSPSS נציגת,ג'ניוס מערכות בע"מ