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What are the Chances? Probability and Uncertainty in Statistics
This course focuses on how analysts can measure and describe the confidence they have in their findings. The course begins with an overview of the key probability rules and concepts that govern the calculation of uncertainty measures. We’ll then apply these ideas to variables (which are the building blocks of statistics) and their associated probability distributions. The second half of the course will delve into the computation and interpretation of uncertainty. We’ll discuss how to conduct a hypothesis test using both test statistics and confidence intervals. Finally, we’ll consider the role of hypothesis testing in a regression context, including what we can and cannot learn from the statistical significance of a coefficient. By the end of the course, you should be able to discuss statistical findings in probabilistic terms and interpret the uncertainty of a particular estimate.
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Rating | Not enough ratings |
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Length | 5 weeks |
Effort | 4 weeks of study, 2-4 hours per week |
Starts | Jul 3 (46 weeks ago) |
Cost | $49 |
From | Johns Hopkins University via Coursera |
Instructor | Jennifer Bachner, PhD |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Social Sciences Data Science Business |
Tags | Social Sciences Data Science Data Analysis Economics |
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Rating | Not enough ratings |
---|---|
Length | 5 weeks |
Effort | 4 weeks of study, 2-4 hours per week |
Starts | Jul 3 (46 weeks ago) |
Cost | $49 |
From | Johns Hopkins University via Coursera |
Instructor | Jennifer Bachner, PhD |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Social Sciences Data Science Business |
Tags | Social Sciences Data Science Data Analysis Economics |
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