This course provides a data-oriented introduction to applied statistics, covering exploratory data analysis, experimental design, probability distributions, simulation, sampling distributions, and the Central Limit Theorem. Students will learn the fundamentals of statistical inference, including confidence intervals and hypothesis tests for population means, paired and independent comparisons of means, analysis of variance, and regression. The course emphasizes hands-on experience with statistical software and is primarily intended for students majoring in the mathematical sciences. Prerequisite: two semesters of college calculus.
Learning Outcomes
1Understand basic terms, graphs, and symbols and be able to interpret statistics in the media.
2Understand and be able to explain statistical processes and be able to fully interpret statistical results.
3Understand why and how statistical investigations are conducted and the "big ideas" that underlie statistical investigations.
4Be able to use a statistical package (R or SAS) to analyze data and interpret result.
5Big Ideas in Statistics: variability, distributions, and models; causation vs correlation; practical significance vs statistical significance, etc.
Course STAT 350 from Purdue University - West Lafayette.
