Making Sense of Statistics: A Non-mathematical Approach

Contents......Page 3
List of Figures......Page 7
List of Tables......Page 9
Preface......Page 11
1.1 Statistics......Page 12
1.2 The difficulties of statistics......Page 14
1.3 Non-mathematical methods......Page 16
1.4 Bucket and ball models and computer simulation......Page 18
1.5 Numbers, calculators and computers......Page 21
1.6 Suggestions for studying statistics and using this book......Page 22
2.1 Probability......Page 27
2.2 What do the balls and buckets represent?......Page 30
2.3 Where do probabilities come from?......Page 31
2.5 Sampling......Page 32
2.6 Similar concepts......Page 36
2.7 Exercises......Page 37
2.8 Summary of main points......Page 38
3.1 Introduction......Page 39
3.2 What can a sample tell us about?......Page 40
3.3 Variables, cases and units of analysis......Page 41
3.4 Summarising a single variable......Page 42
3.5 Summarising the relation between two category variables......Page 50
3.7 Summarising the relation between two number variables......Page 51
3.8 Summarising the relation between three or more variables......Page 59
3.9 Beyond the data: cause, effect and the wider context......Page 60
3.10 Similar concepts......Page 62
3.11 Exercises......Page 63
3.12 Summary of main points......Page 65
4.1 Introduction......Page 66
4.2 Characteristic features of the statistical approach......Page 67
4.3 What sort of conclusions does statistics provide?......Page 68
4.4 What are the alternatives to statistics?......Page 70
4.5 Anecdotes about specific cases......Page 71
4.6 Fuzzy logic......Page 72
4.7 Chaos......Page 74
4.9 Summary of main points......Page 78
5.1 Working out probabilities by listing equally likely possibilities......Page 80
5.2 Working out probabilities by thought experiments: the lots of times tactic......Page 81
5.3 Working out probabilities by computer simulation......Page 86
5.4 Simulating distributions of probabilities: the two bucket model......Page 88
5.5 The Poisson distribution: counts of random events......Page 92
5.6 The normal distribution......Page 96
5.8 Exercises......Page 101
5.9 Summary of main points......Page 103
6.1 Introduction......Page 105
6.2 An experiment on telepathy......Page 106
6.4 Bayes\' principle: the pruned ball method......Page 107
6.6 Null hypothesis testing......Page 112
6.7 Exercises......Page 114
6.8 Summary of main points......Page 115
7.1 Introduction......Page 116
7.2 Bootstrap confidence intervals......Page 117
7.3 Large populations: does size matter?......Page 123
7.4 What is the smallest sample we can get away with?......Page 124
7.5 Other statistics: proportions, quartiles, correlations and so on......Page 126
7.6 Assumptions behind bootstrap confidence intervals: what to check for......Page 128
7.7 Similar concepts......Page 129
7.8 Exercises......Page 130
7.9 Summary of main points......Page 132
8.1 An example: testing the hypothesis that a doctor is not a murderer......Page 133
8.2 General procedure and rationale for null hypothesis tests......Page 135
8.3 Testing a hypothesis that there is no relationship......Page 136
8.4 An alternative: confidence intervals for a relationship......Page 142
8.5 The interpretation of p values......Page 144
8.6 Why p values can be misleading: things to watch for......Page 146
8.7 Choosing a method of inference: p values and other approaches......Page 149
8.8 Similar concepts......Page 150
8.9 Exercises......Page 152
8.10 Summary of main points......Page 153
9.1 Introduction: predicting earnings on the Isle of Fastmoney......Page 154
9.2 Straight line prediction models: linear regression......Page 156
9.3 Assessing the accuracy of prediction models......Page 162
9.4 Prediction models with several independent variables: multiple regression......Page 165
9.5 Using the regression procedures in Excel and SPSS......Page 170
9.6 Things to check for with regression......Page 171
9.7 Cause, effect, prediction and explanation......Page 173
9.8 Similar concepts......Page 175
9.9 Exercises......Page 176
9.10 Summary of main points......Page 177
10.1 The logic of empirical research: surveys, experiments and so on......Page 178
10.2 The practicalities of doing empirical research......Page 183
10.3 Interpreting statistical results and solving problems......Page 185
10.4 Similar concepts......Page 187
10.5 Exercises......Page 188
A. Using spreadsheets (Excel) for statistics......Page 189
A.2 Random number functions: generating samples and probabilities......Page 191
A.4 Pivot Table reports......Page 192
A.7 Producing a histogram......Page 193
B.1 Data entry......Page 194
B.2 Analysis: commonly used methods......Page 195
C. Data and program files for downloading......Page 196
D. Comments on some of the exercises......Page 198
Notes......Page 203
References......Page 212
B......Page 213
D......Page 214
L......Page 215
O......Page 216
R......Page 217
S......Page 218
V......Page 219
Y......Page 220