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- DISCOVERING STATISTICS USING IBM SPSS STATISTICS 5TH EDITION HOW TO
- DISCOVERING STATISTICS USING IBM SPSS STATISTICS 5TH EDITION MAC
Comparing Two Means Looking for differences An example: are invisible people mischievous? Categorical predictors in the linear model The t-test Assumptions of the t-test Comparaing two means: general procedure Comparing two independent means using IBM SPSS Statistics Comparing two related means using IBM SPSS Statistics Reporting comparisons between two means Between groups or repeated measures?Chapter 11. Linear Model (Regression) An introduction to the linear model (regression) Bias linear models? Generalizing the model Sample size and the linear model Fitting linear models: the general procedure Using IBM SPPS Statistics to fit a linear model with one predictor Interpreting a linear model with one predictor Interpreting a linear model with two or more predictors (multiple regression) Using IBM SPSS Statistics to fit a linear model with several predictors Interpreting a linear model with several predictors Robust regression Bayesian regression Reporting linear modelsChapter 10.
DISCOVERING STATISTICS USING IBM SPSS STATISTICS 5TH EDITION HOW TO
Correlation Modeling relationships Data entry for correlation analysis Bivariate correlation Partial and semi-partial correlation Comparaing correlations Calculating the effect size How to report correlation coefficentsChapter 9. Non-Parametric Models When to use non-parametric tests General procedure of non-parametric tests in SPSS Comparing two independent conditions: the Wilcoxon rank-sum test and Mann-Whitney test Comparing two related conditions: the Wilcoxon signed-rank test Differences between several independent groups: the Kruskal-Wallis test Differences between several related groups: Friedman's ANOVAChapter 8.
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The Beast of Bias What is bias? Outliers Overview of assumptions Additivity and linearity Normally distributed something or other Homoscedasticity/homogeneity of variance Independence Spotting outliers Spotting normality Spotting linearity and heteroscedasticity/heterogeneity of variance Reducing biasChapter 7. Exploring Data With Graphs The art of presenting data The SPSS Chart Builder Histograms Boxplots (box-whisker diagrams) Graphing means: bar charts and error bars Line charts Graphing relationships: the scatterplot Editing graphsChapter 6.
DISCOVERING STATISTICS USING IBM SPSS STATISTICS 5TH EDITION MAC
The IBM SPSS Statistics Environment Versions of IBM SPSS Statistics Windows, Mac OS, and Linux Getting started The data editor Entering data into IBM SPSS Statistics Importing data The SPSS viewer Exporting SPSS output The syntax editor Saving files Opening files Extending IBM SPSS StatisticsChapter 5. The Phoenix of Statistics Problems with NHST NHST as part of wider problems with science A phoenix from the EMBERS Sense, and how to use it Pre-registering research and open science Effect size Bayesian approaches Reporting effect sizes and Bayes factorsChapter 4. The Spine of Statistiscs What will this chapter tell me? What is the SPINE of statistics? Statistical models Populations and samples P is for parameters E is for estimating parameters S is for standard error I is for (confidence) interval N is for null hypothesis significance testing Reporting significance testsChapter 3. Why is My Evil Lecturer Forcing Me to Learn Statistics? What the hell am I doing here? I don't belong here The Research Process Initial observation: finding something that needs explaining Generating and testing theories and hypotheses Collecting data: measurement Collecting data: research design Analysing data Reporting dataChapter 2.