BMR 617: Statistical Techniques for the Biomedical Sciences

This course is intended for students in the Biomedical Research Ph.D. program. Students in this course will learn the basics of data exploration, presentation, and analysis suitable for biomedical researchers. We will focus on interpretation of data, and on presenting results in a form suitable for publication in peer-reviewed manuscripts.

Class time:
Monday, Wednesday, and Friday 10-10:50 am
Class meeting room:
By videoconference due to the COVID-19 pandemic

Course director and instructor: James Denvir, Ph.D.
Office:
BBSC 336R
Phone:
304-696-7327

Course instructor: Andrew Nato, Ph.D.
Office:
BBSC 336M
Phone:
304-696-3562
This course will use online materials; there is no text book. Class time will typically involve students sharing material they about which they were confused or had questions, with discussion, and a preview by the instructor(s) of the material to be covered before the next class.
Students will use the R statistical computing environment for data analysis and visualization. For help with R and RStudio, use the R Resources button on the navigation bar, in addition to material provided in class.
DateLectureR CodeRecording
January 12th 2022 Installing and Intro to R intro.R
January 14th 2022 Types of variable types.R 2022-01-14.mp4
January 19th 2022 Exploring distributions, averages, and spread MeanMedianSpread.R 2022-01-19.mp4
January 21st 2022 The normal distribution NormalDistribution.R 2022-01-21.mp4
January 24th 2022 Data Wrangling DataWrangling.R
January 28th 2022 Introduction to Graphing with ggplot2 GraphingCQ.R
January 31st 2022 Relative and Attributable Risks R_A_Risks.R
February 2nd 2022 Correlation Correlation.R
February 4th 2022 Class canceled due to weather and road conditions  
February 7th 2022 Part 1 Review Create_Read_CSV.R
February 9th 2022 Probability
February 11th 2022 Samples and Distributions Error_Bars.R
February 14th 2022 Point estimation of the mean and introduction to confidence intervals IntroConfIntervals.R
February 16th 2022 Confidence Intervals ConfidenceIntervals.R 2022-02-16.mp4
February 18th 2022 Confidence Intervals for Proportions 2022-02-18.mp4
February 21st 2022 Hypothesis Testing IntroHypothesisTesting.R
February 23rd 2022 Hypothesis Testing for a Single Proportion 2022-02-23.mp4
Matrices, data frames, and tables in R
February 25th Comparing Proportions ComparingProportions.R
February 28th Hypothesis Testing for Population Mean HypothesisTestingPopulationMean.R
March 2nd Inference: Two-Class t-test TwoSample_t-test.R
March 4th Inference: Matched Pairs t-test Paired_t-test.R
March 9th Review 2
March 21st One-way ANOVA OneWayANOVA.R 2022-03-21.mp4
March 23rd Two-way ANOVA TwoWayANOVA.R
March 28th Linear Regression LinRegCovid.R
March 30th Multiple Linear Regression MultLinReg.R 2022-03-30.mp4
April 1st Linear Models LinModels.R
April 4th Sample Size and Power Exploration in R
April 6th Review 3
April 11th Writing Journal Articles (part 1)
April 13th Writing Journal Articles (part 2) Cholesterol.R 2022-04-13.mp4
April 15th R Notebooks Cholesterol.Rmd
April 18th Multiple Hypothesis Testing
WorkshopModel solutionR code
Installing R and R studio:
  • Home page and download for R (install R first from here)
  • R Studio (install the free version of R Studio from here, after installing R)
These are some (of very many) free online tutorials available which make good background reading: