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
David is a Data Scientist at U.Group, leveraging data to address complex business problems, identify user needs, and amplify the abilities of everyone to find solutions. He is an enthusiastic collaborator who values working with others. Before joining U.Group, David spent 9 years as a high school...
Read more about Business Analytics
Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.