The purpose of this thesis is to develop a methodology whereby a large volume and variety of population data can be selected and organized to present a comprehensive picture of the settlements in Manitoba. In particular, 74 variables are used to analyse the socio-economic and demographic conditions of the 90 major settlements. The main source of data is the 1961 Dominion Bureau of Statistics Census Enumeration Area 'print-outs'. The data are arranged in the form of a matrix and analysed statistically with the aid of a computer. The analysis is conducted in the following steps; (a) the inter-relationships of the 74 variables are studied systematically by means of correlation analysis; (b) the settlements are then classified into groups according to their regional distribution, population size and change, family income and economic functions, and the variation of these characteristics between the settlement groups are examined; and (c) a multivariate analytic approach is applied to the data matrix in order to indentify a set of basic, independent dimensions for the settlements. Based on these resulting dimensions, a system of classification and a principal component regression model is designed. The results of the analysis indicate that the settlements behave like interdependent entities of a general system because they are characterised by patterns and associations of functionally interrlated variables. The demographic characteristics such as the age structure of settlements are statistically related to many socio-economic variables. For example, settlements with an aged population structure are generally associated with a large proportion of population immigrated to Canada before 1946, and their labour force is made up of a large percentage of self-employed and unpaid family workers engaged mainly in agriculture and tertiary industries. On the other hand, settlements with a younger population structure are associated with a rapid rate of population growth, a relatively large family size and location in the northern parts of the province...