Statistics for Data Science

3 credits · Undergraduate

Introduction to descriptive and inferential statistics using computational and resampling approaches from data science. Probability, measurement, random variables, distributions, central tendency, variability, confidence intervals, measures of uncertainty, estimation, prediction, hypothesis testing and inference, replicability, power, effect size, t-tests, correlation, univariate ANOVA, and simple linear regression. Examples from wide range of disciplines. [3]