Statistics

This course introduces the nature of probability and statistics, data organization, frequency
distributions and graphs, descriptive measures, basic probability and counting rules, discrete
probability distributions, the normal distribution, and introductory confidence intervals.

This course introduces the basic concepts of descrip2ve and inferen2al sta2s2cs used in science and
engineering. The course teaches (1) how to use data to make numerical conjectures about biological,
medical and agricultural problems; (2) how to summarize and analyze data and interpret the results.
Topics include histograms, average, standard devia2on, the normal curve, linear regression,
es2ma2on, correla2on, confidence intervals, hypothesis tes2ng, measurement error and tests of
sta2s2cal significance.

Prerequisite Courses: MAT 112 OR MAT 116

The course covers the fundamentals of statistical computing and data analysis in R environment; How to code in R studio by using basic functions or by writing custom R functions, how to use R for analytical programming, how to create data visualizations, how to handle large data, how to implement Probability and Probability Distributions/sampling to solve a wide variety of problems, how to conduct and interpret a variety of hypothesis tests to make decisions, how to create, analyze and interpret regressions and correlations underlying relationships between different variables in multivariate context for predictive purpose.