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Biostatistics is an essential skill for every public health researcher because it provides a set of precise methods for drawing meaningful conclusions from data. In this second course of the Specialization in Biostatistics in Public Health, you will learn to evaluate the variability of the sample and apply statistical hypothesis testing methods. Along the way, he will perform calculations and interpret real-world data from the published scientific literature. Topics include sample statistics, the central limit theorem, confidence intervals, hypothesis tests, and p-values.
Sampling distributions and standard errors
Confidence intervals for single population parameters
Two-Group Hypothesis Test: The General Concept and the Means of Comparison
Hypothesis test (comparison of proportions and incidence rates between two populations) and extended hypothesis test
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Associate Scientist, Biostatistics
Bloomberg School of Public Health
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