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About the course
In today’s world, there is no shortage of data. But the quantity of information means nothing without the ability to understand it. This course teaches you statistical thinking concepts that are essential for learning from data and communicating insights. By the end of the course, you will be able to perform exploratory data analysis, understand the key principles of sampling, and select appropriate tests of significance for multiple contexts. You will gain the foundational skills that prepare you to pursue more advanced topics in statistical thinking and machine learning.
- Descriptive Statistics for Exploring Data
- Sampling and Randomized Controlled Experiments
- Introduction to Probability
- Sampling Distributions and the Central Limit Theorem
- Common Tests of Significance
- Multiple Comparisons
Trust the experts
Guenther Walther studied mathematics, economics, and computer science at the University of Karlsruhe in Germany and received his Ph.D. in Statistics from UC Berkeley in 1994. His research has focused on statistical methodology for detection problems, shape-restricted inference, and mixture analy...