Module 3 Overview (1:07)

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Johns Hopkins University
Statistics for Genomic Data Science
Johns Hopkins University

4.2 (333 ratings)

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32K Students Enrolled

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Skills You'll Learn

Statistics, Data Analysis, R Programming, Biostatistics

Reviews

4.2 (333 ratings)

  • 5 stars
    54.05%
  • 4 stars
    27.02%
  • 3 stars
    11.71%
  • 2 stars
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  • 1 star
    4.80%

TK

Mar 24, 2019

Very good course and useful understanding statistical aspects of data.

HD

Apr 8, 2021

This is the best. It opens my eye for genomic data analysis.

From the lesson

Module 3

This week we will cover modeling non-continuous outcomes (like binary or count data), hypothesis testing, and multiple hypothesis testing.

Module 3 Overview (1:07)1:07
Logistic Regression (7:03)7:03
Regression for Counts (5:02)5:02
GLMs in R (9:28)9:28
Inference (4:18)4:18
Null and Alternative Hypotheses (4:45)4:45
Calculating Statistics (5:11)5:11
Comparing Models (7:08)7:08
Calculating Statistics in R9:46
Permutation (3:26)3:26
Permutation in R (3:33)3:33
P-values (6:04)6:01
Multiple Testing (8:25)8:25
P-values and Multiple Testing in R: Part A (5:58)5:58
P-values and Multiple Testing in R: Part B (4:23)4:23

Taught By

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    Jeff Leek, PhD

    Associate Professor, Biostatistics

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