• Estimation of size of national and sub-national populations

• Estimation of demographic rates, and incidence and prevalence rates of various diseases

• Causal analysis of concurrent and sequential variations in vulnerability to various risks

• Operations research in which one wants to know whether a programme has been effective in achieving the desired goal (such as promoting safe sex practices, reducing stigma against HIV and rehabilitation of people living with AIDS)

• Descriptive studies of knowledge, attitudes and practices like family planning methods

• Rapid situation analysis and benchmarking

Quantitative survey research seems to be best suited for obtaining hard facts and factual descriptive information that is the keystone for most social scientific research. Qualitative research is not amenable to study many important research issues such as measurement of attitudes in various domains and for different purposes, study of demographic patterns, behaviour patterns pertaining to health and illness, evaluation of community intervention programmes, religious beliefs and their causal influence on social behaviour, etc. to mention only a few. Most research problems involve intricate relationships among variables. Such relationships involve various complex formats and structures. Tacq (1997) provides a comprehensive discussion of such structures and corresponding multivariate statistical techniques of analysis. The format of multivariate analysis techniques may involve convergent causal structure, interactive structure, spurious or indirect causality, discriminant structure, canonical structure and latent structure, among others. The complex reality of social scientific problems is thus dealt with to a great extent by multivariate techniques.