Managerial Statistics I

3 units

The first of a two-course sequence in business applications of statistics, focused on descriptive statistics, probability and distributions, inferential statistics, and linear regression. Approximately, the first third of the course covers descriptive statistics and predictive analytics, including data visualization, applications of covariance, Simple Linear Regression, and Machine Learning in R. The second third is devoted to probability: basic rules, conditional probabilities, Bayes' theorem, expected values, and probability distributions. This work is followed by an introduction to sampling distributions and inferential statistics in the final third of the course. Confidence intervals and hypothesis testing are introduced to make inferences about parameters. Students are also introduced to Data Analytics using Python. Software used in the course includes Excel, R Studio, Tableau, and Python.