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About the course
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.
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