Chapter 3 Some Basic Statistical Measures 3.1 Purpose The purpose of this chapter is to introduce some basic statistical measures that are commonly used in demographic analysis. The concepts are defined in general terms without going into theoretical details. Methods of calculation of various measures are described. The statistical measures discussed in this chapter consist of counts, frequencies, proportions, rates, various measures of central tendency, dispersion, comparison, correlation and regression. 3.2 Demographic Data and Analysis Demographic data can be classified according to their level of measurement. This is useful because the level of measurement helps the selection of what statistical analysis is most appropriate. Several classifications can be used. This book uses the four-fold classification system proposed by Stevens (1946) that classifies data as being (1) nominal, (2) ordinal, (3) interval and (4) ratio. There are other systems such as the two-fold classification of (1) discrete and (2) continuous. In the classification system proposed by Stevens, the nominal level is known as the lowest level of measurement. Here, the values just name the attribute uniquely and do not imply an ordering of cases. For example, the variable marital is inherently nominal. In a study it might be useful to have attributes such as never married, married, separated, divorced and widowed. These attributes are mutually exclusive and exhaustive. They could be coded N, M, S, D and W respectively, or coded as 1, 2, 3, 4 and 5. In the latter, the numbers are not numbers in a real sense since they cannot be added or subtracted. Thus, numbers assigned to serve as values for nominal level variables such as marital status cannot be added, subtracted, multiplied or divided in a meaningful way. An exception is the dummy coding of F. Yusuf et al., Methods of Demographic Analysis, DOI 10.1007/978-94-007-6784-3_3, © Springer Science+Business Media Dordrecht 2014 21