Experimental Design and Statistical Analysis for Pharmacology and the Biomedical Sciences
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