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Klappentext Dancey and Reidy are very well known for their Pearson textbook Statistics Without Maths for Psychology and have applied the same principles here to the health sciences market, where they're far more established as researchers. Zusammenfassung Dancey and Reidy are very well known for their Pearson textbook Statistics Without Maths for Psychology and have applied the same principles here to the health sciences market, where they're far more established as researchers. Inhaltsverzeichnis PART ONE: AN INTRODUCTION TO THE RESEARCH PROCESS Overview The Research Process Concepts and Variables Levels of Measurement Hypothesis Testing Evidence-Based Practice Research Designs Multiple-Choice Questions PART TWO: COMPUTER-ASSISTED ANALYSIS Overview Overview of the Three Statistical Packages Introduction to SPSS Setting out Your Variables for within - and between-Group Designs Introduction to R Introduction to SAS Summary Exercises PART THREE: DESCRIPTIVE STATISTICS Overview Anaylsing Data Descriptive Statistics Numerical Descriptive Statistics Choosing a Measure of Central Tendency Measures of Variation or Dispersion Deviations from the Mean Numerical Descriptives in SPSS Graphical Statistics Bar Charts Line Graphs Incorporating Variability into Graphs Generating Graphs with Standard Deviations in SPSS Graphs Showing Dispersion - Frequency Histogram Box-Plots Summary SPSS Exercise Multiple Choice Questions PART FOUR: THE BASIS OF STATISTICAL TESTING Overview Introduction Samples and Populations Distributions Statistical Significance Criticisms of NHST Generating Confidence Intervals in SPSS Summary SPSS Exercise Multiple Choice Questions PART FIVE: EPIDEMIOLOGY Overview Introduction Estimating the Prevalence of Disease Difficulties in Estimating Prevalence Beyond Prevalence: Identifying Risk Factors for Disease Risk Ratios The Odds-Ratio Establishing Causality Case-Control Studies Cohort Studies Experimental Designs Summary Multiple Choice Questions PART SIX: INTRODUCTION TO DATA SCREENING AND CLEANING Overview Introduction Minimising Problems at the Design Stage Entering Data into Databases/Statistical Packages The Dirty Dataset Accuracy Using Descriptive Statistics to Help Identify Errors Missing Data Spotting Missing Data Normality Screening Groups Separately Reporting Data Screning and Cleaning Procedures Summary Multiple Choice Questions PART SEVEN: DIFFERENCES BETWEEN TWO GROUPS Overview Introduction Conceptual Description of the t-Tests Generalising to the Population Independent Groups t-Test in SPSS Cohen¿s d Paired t-Test in SPSS Two-Sample z-Test Non-Parametric Tests Mann-Whitney: for Independent Groups Mann-Whitney Test in SPSS Wilcoxon Signed Rank Test: For Repeated Measures Wilcoxon Signed Rank Test in SPSS Adjusting for Multiple Tests Summary Multiple Choice Questions PART EIGHT: DIFFERENCES BETWEEN THREE OR MORE CONDITIONS Overview Introduction Conceptual Description of the (Parametric) ANOVA One-Way ANOVA One-way ANOVA in SPSS ANOVA Models for Repeated-Measures Designs Repeated Measures ANOVA in SPSS Non-parametric Equivalents The Kruskal-Wallis Test Kruskal-Wallis and the Median Test in SPSS The Median Test Friedman¿s ANOVA for Repeated Measures Friedman¿s ANOVA in SPSS Summary Multiple Choice Questions PART NINE: TESTING ASSOCIATIONS BETWEEN CATEGORICAL VARIABLES Overview Introduction Rationale of Contingency Table Analysis Running the Analysis in SPSS Measuring Effect Size in Contingency Table Analysis Larger Conting...
