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所在平台: Edx |
课程主页: https://www.edx.org/course/probability-and-statistics-iv-confidence-intervals-and-hypothesis-tests
课程评论：没有评论
Learners will be expected to come in knowing some set theory and basic calculus, as well as the material from the previous courses in this series ( A Gentle Introduction to Probability , Random Variables, and A Gentle Introduction to Statistics ). The prerequisite material is all available for you to access; and in any event, we will make the current course as self-contained as possible. In addition, this course will involve a bit of computer programming, so it would be nice to have at least a little experience in something like Excel and/or the R freeware statistical package.
This course covers two important methodologies in statistics – confidence intervals and hypothesis testing.
Confidence intervals are encountered in everyday life, and allow us to make probabilistic statements such as: “Based on the sample of observations we conducted, we are 95% sure that the unknown mean lies between A and B,” and “We are 95% sure that Candidate Smith’s popularity is 52% +/- 3%.” We begin the course by discussing what a confidence interval is and how it is used. We then formulate and interpret confidence intervals for a variety of probability distributions and their parameters.
Hypothesis testing allows us to pose hypotheses and test their validity in a statistically rigorous way. For instance, “Does a new drug result in a higher cure rate than the old drug?” or “Is the mean tensile strength of item A greater than that of item B?” The second half the course begins by motivating hypothesis tests and how they are used. We then discuss the types of errors that can occur with hypothesis testing, and how to design tests to mitigate those errors. Finally, we formulate and interpret hypothesis tests for a variety of probability distributions and their parameters.
