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This course will cover foundational concepts in descriptive analyses, probability, and statistical inference. Topics to be covered include data exploration through descriptive statistics (with a heavy emphasis on using R for such analyses), elementary probability, diagnostic testing, combinatorics, random variables, elementary distribution theory, statistical inference, and statistical modeling. The inference portion of the course will focus on building and applying hypothesis tests and confidence intervals for population means, proportions, variances, and correlations. Non-parametric alternatives will also be introduced. The modeling portion of the course will include ANOVA, and simple and multiple regression and their respective computational methods. Students will be introduced to the R statistical computing environment. This course is FULLY ONLINE and ASYNCHRONOUS.
PREREQUISITES: MATH 150 or MATH 150A; and MATH 142 or MATH 161 or MATH 171 (or equivalent discrete mathematics and calculus)
- Location
- Asynchronous Online (ASE)
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