Making Sense of Data: Introduction to Statistical Inference

1 credits · Graduate

We are often presented with a set of data, often very large, about various processes or phenomena (health data, economic performance, environmental indices, experimental observations). How do we make sense of them? We will describe various statistical tools that will allow us to draw meaningful conclusions (inference). Topics covered include various distribution functions and criteria for their selection (goodness of fit), descriptive statistics compressing the data, estimation of various parameters from the data, measures of relationships between different datasets (correlation, regression), and data related in time (time series).