An Introduction to Quantitative Methods for Historians

Many statements made by historians are quantitative statements, involving the use of measurable historical evidence. The historian who uses quantitative methods to analyse and interpret such information needs to be well acquainted with the particular methods and techniques of analysis and to be able to make the best use of the data that are available. There is an increasing need for training in such methods and in the interpretation of the large volume of literature now using quantitative techniques. Dr Flouds text, which is relevant to all branches of historical inquiry, provides a straightforward and intelligible introduction for all students and research workers. The simpler and more useful techniques of descriptive and analytical statistics are described, up to the level of simple linear regression. Historical examples are used throughout, and great attention is paid to the need to ensure that the techniques are consistent with the quality of the data and with the historical problems they are intendedto solve. Attention is paid to problems of the analysis of time series, which are of particular use to historians. No previous knowledge of statistics is assumed, and the simple mathematical techniques that are used are fully and clearly explained, without the use of more mathematical knowledge than is provided by an O-level course. A bibliography is provided to guide historians towards the most useful further reading. This student friendly text was first published in 1973.

Preface page xi Introduction 1 1 Classifying historical data 7 (a) Nominal data 8 (b) Ordinal data 10 (c) Interval or ratio data 11 (d) Some complications 12 2 Arranging historical data 16 (a) The data set 16 (b) The case 17 (c) The variable 17 (d) The data matrix 18 (e) Collecting data 22 3 Some simple mathematics 27 (a) The frequency distribution 27 (b) Summation notation 33 (c) Logarithms 37 4 The preliminary analysis of data, I: frequency distributions and charts 42 (a) The frequency distribution 43 (b) Cross-classification 48 (c) Charts page 51 (d) Ratio scale graphs 59 5 The preliminary analysis of data, II: summary measures 67 (a) The arithmetic mean 67 (b) The standard deviation 72 (c) The geometric mean 77 (d) The median 77 (e) The mode 81 (f) The coefficient of variation 82 (g) Which to use? 82 6 The analysis of time series 85 (a) Objects and assumptions of the analysis of time series 87 (b) The rate of growth 90 (c) The trend 93 (d) Regular fluctuations in time series 108 (e) The use of ratios and index numbers 117 7 Relationships between variables 125 (a) Is there a relationship? 127 (b) How strong is the relationship? 138 (c) The form of relationships 140 (d) Correlation and regression with time series data 152 8 The problem of imperfect data 155 (a) Too much information: the selection of variables 157 (b) Too much information: the selection of cases 161 (c) The '¬~significance' of sample results 171 (d) Too few data: the problems of missing data 175 (e) Data missing on one or more cases 176 (f) Data missing on one or more variables 178 (g) Data missing on one or more variables of one or more cases, but not on any complete case or variable 182 9 Computers and data processing equipment page 184 (a) Calculating machines 184 (b) Punched card data processing equipment 186 (c) The electronic computer 190 Bibliography 209 Logarithms 212 Antilogarithms 214 Index 216