In this course, a student will be taken through revision on probability mass function; probability density functions: definition and rules, cumulative distribution functions, mean, median variance, standard deviation and coefficient of variation; Joint probability distribution functions: Marginal probability functions, conditional probability distribution functions and independent random variables; Expectations, Moment generating functions and moments, Cumulant generating functions and cumulants; Characteristic functions; Function of random variables and convolution.
- Lecturer: Dr Dibaba Gemechu
Welcome to the world of Biostatistics. This course will help you understand public health research in terms of research designs, measures of disease risk, statistical modeling with public health data and survival analysis. We introduce to a family of models called GLMs, Generalised Linear Regression models such as logistic and Poisson regression models. Of importance will be the estimation of parameters, making appropriate inferences on these parameters and the explanatory variables. Model diagnostics will be delt with in detail to enable you to assess the goodness of fit of your models before you publish results that are based on these models. Hope you will enjoy the course!!!
- Lecturer: Dr Dibaba Gemechu