Major Areas of Study

Exploring and Understanding Data and Relationships Among Variables : exploratory analysis of data makes use of graphical and numerical techniques to study patterns and departures from patterns. Graphical and numerical displays and summaries can be used to highlight such patterns and deviations.

Topics Include : Types of Data, Graphs and Numerical Summaries of Data, The Normal Model, Standardized Scores, Scatterplots, Association, and Correlations, Qualitative Variables and Related Models.

Gathering Data : Data must be collected according to a well-developed plan if valid information on a conjecture is to be obtained. This plan includes clarifying the question and deciding upon a method of data collection and analysis.

Topics Include : Random Number Generation, Sampling Methods, Types of Bias, Experimental Design.

Randomness and Probability : Probability is a tool used for anticipating what the distribution of data should look like under a given model.

Topics Include : Probability Rules, Random Variables, Probability Models.

Introduction to Inferential Statistics : Statistical inference guides the selection of appropriate models.

Topics Include : Sampling Distribution Models, Confidence Intervals for Proportions, Testing Hypothesis About Proportions, Inferences About Means.