Mathematical Biostatistics Boot Camp 2

开始时间: 09/21/2015 持续时间: 7 weeks

所在平台: Coursera

课程类别: 统计和数据分析

大学或机构: Johns Hopkins University(约翰•霍普金斯大学)

授课老师: Brian Caffo



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This class presents fundamental concepts in data analysis and statistical inference, focusing on one and two independent samples. Students having taken this class should be able to summarize samples, perform relevant hypothesis tests and perform a collection of two sample comparisons. Classical non-parametric methods and discrete data analysis methods are discussed.  The class is taught at a master's of biostatistics introductory level and requires Mathematical Biostatistics Boot Camp 1 as a prerequisite.


  • Hypothesis Testing
  • Power and sample size and two group tests
  • Tests for binomial proportions
  • Two sample binomial tests, delta method
  • Fisher's exact tests, Chi-squared tests
  • Simpson's paradox, confounding
  • Retrospective case-control studies, exact inference for the odds ratio
  • Methods for matched pairs, McNemar's, conditional versus marginal odds ratios
  • Non-parametric tests, permutation tests
  • Inference for Poisson counts
  • Multiplicity


Deep Learning Specialization on Coursera


Learn fundamental concepts in data analysis and statistical inference, focusing on one and two independent samples.


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