MAT 201 Introduction to Statistics
This computer-based course presents the main concepts in Statistics: the concept of random variables, frequency, and probability distributions, variance and standard deviation, kurtosis and skewness, probability rules, Bayes theorem, and posterior probabilities. Important statistical methods like Contingency analysis, ANOVA, Correlation analysis and Regression Analysis are introduced and their algorithms are fully explained. The most important probability distributions are introduced: Binomial, Poisson, and Normal distribution, as well as the Chebyshev theorem for non-known distributions. Inferential statistics, sampling distributions, and confidence intervals are covered to introduce statistical model building and single linear regression. Active learning and algorithmic learning are stressed.
Emphasis is put both on algorithms –methods and assumptions for their applications. Excel is used while calculators with STAT buttons are not allowed. Ultimately students are required to make a month-long research project, select the theoretical concept they want to test, perform a literature review, find real data from Internet databases or make their surveys, apply methods they studied in the class, and compare theoretical results with their findings. Research is done and presented in groups, papers are Individual. Selected SPSS or Excel Data Analysis examples are also provided.