XBUS-504 Data Analysis I: Statistics

The fields of statistics and probability were founded on empirical analysis of data (e.g. human height). Data scientists must possess a strong foundation in statistics and probability to uncover patterns and build models, algorithms, and simulations. This course reviews the basics of descriptive and inferential statistics, distributions, probability, and regression with a specific focus on application to real data sets.

Course Objectives

Upon successful completion of the course, students will:

• Explain descriptive and inferential statistics
• Compute measures of central tendency, variance, and probabilities
• Produce and interpret meaningful and accurate summary statistics for a given data set
• Conduct hypothesis tests and understand the difference between Type I and Type II errors
• Develop single and multivariate regression models
• Differentiate between correlation and causation