Model building in regression analysis

Regression analysis is an increasingly used statistical technique for examining and modeling the relationship between various phenomena, which evolves formulation of a mathematical expression that characterizes the behavior of a particular random variable and its dependence on the set of external factors. The fundamental goal of the thesis is to illustrate the main steps of the model-building procedure, enhance understanding of the least squares estimation technique, and associated statistical methods. The emphasis of the theoretical part is placed on the discussion of the essential linear regression concepts and provision of tools necessary for utilizing a modeling approach for statistical analysis of the response variable. The practical part of the thesis aims at the illustration of the regression model-building process implemented using the actual data on the life expectancy at birth in various countries in order to investigate its dependence on the socio-economic development, demographic indicators, immunization coverage, nutritional status, and risk factors. The regression analysis is entirely conducted in the R statistical computing environment, which provides a broad spectrum of statistical and graphical techniques.