Experimental Design and Statistical Analysis for Pharmacology and the Biomedical Sciences. Paul J. Mitchell
Table of Contents
1 Cover
6 Acknowledgements Homo Sapiens – Part 1 Statistical Packages Homo Sapiens – Part 2
7 Foreword
8 1 Introduction Experimental design: the important decision about statistical analysis Statistical analysis: why are statistical tests required? The eye‐ball test! The structure of this book: Descriptive and Inferential Statistics
9 2 So, what are data? Data handling and presentation
10 3 Numbers; counting and measuring, precision, and accuracy Precision and accuracy Errors in measurement Independent observations or duplicate/triplicate/quadruplicate? That is the question!
11 4 Data collection: sampling and populations, different types of data, data distributions Sampling and populations The Central Limit Theorem Types of data Classification of data distributions So why do we need to understand data distribution?
12 5 Descriptive statistics; measures to describe and summarise data sets Parametric Descriptive Statistics and the Normal Distribution Example output from statistical software
13 6 Testing for normality and transforming skewed data sets Transforming skewed data sets to approximate a normal distribution Removing outliers: Grubbs's test QQ plots Example output from statistical software
14 7 The Standard Normal Distribution
15 8 Non‐parametric descriptive statistics Non‐parametric descriptive statistics Example output from statistical software
16 9 Summary of descriptive statistics: so, what values may I use to describe my data? Introduction: the most important question to answer in statistical analysis! What type of data do I have? Taking the first steps to data description and analysis Strategy for descriptive statistics Example data Example output from statistical software Decision Flowchart 1: Descriptive Statistics – Parametric v Non‐Parametric data
17 10 Introduction to inferential statistics Overview Hypothesis testing Experimental design
18 11 Comparing two sets of data – Independent t‐test The Independent t-test Equal group sizes Unequal group sizes Interpretation of the t statistic Example output from statistical software
19 12 Comparing two sets of data – Paired t‐test The Paired t-test Interpretation of the t statistic Example output from statistical software
20 13 Comparing two sets of data – independent non‐parametric data The Wilcoxon Rank Sum test and Mann-Whitney U-test The Wilcoxon Rank-Sum test The Mann–Whitney U‐test Example output from statistical software
21 14 Comparing two sets of data – paired non‐parametric data The Wilcoxon Signed‐Rank test