MATH132 - Introduction to Data Science and Applied Statistics
Prerequisite(s): MATH 131 or ECON 225
Description: This course begins by introducing Data Science with an overview of current trends in data science, the history of R, how to install R, and an introduction to R programming. Data structure concepts include exploring data visualization with nermical and catagorical data, data transmition, and importing data. The course continues with exploring data analysis including variation, missing values, covariation, patterns, and models. This course concludes with statistical inferences including linear regression with simple/multiple predicators, confidence intervals, hypothesis testing, inference for single mean/proportion, compairing paired means/proportions, many means with ANOVA and machine learning.
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