Course: BIOSTAT 213: Introduction to Computing in the R Software Environment (Winter 2019)

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Introduction to Computing in the R Software Environment BIOSTAT 213 Winter 2019 (1 units). Course Director: Yea-Hung Chen, PhD. Department of Epidemiology and Biostatistics

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Select section Wednesday, January 16, 2019, 1:00--2:30 pm

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Wednesday, January 16, 2019, 1:00--2:30 pm
Module 1: Fundamentals
introduction to R and RStudio
mathematical operators and functions
functions
object assignment
scripts
numeric objects
character objects

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  Aragón TJ. Population Health Data Science with R. bookdown.org: 2018.
  Chapter 1 (you may consider skipping 1.3)
  Chapter 2 (you may consider skipping 2.3, 2.4, and 2.5)
  Grolemund G, Wickham H. R for Data Science. r4ds.had.co.nz: 2018.
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Select section Wednesday, January 16, 2019, 2:30--3:30 pm

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Wednesday, January 16, 2019, 2:30--3:30 pm
Module 1 Lab
Location: Mission Hall 2500
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Select section Wednesday, January 23, 2019, 1:00--2:30 pm

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Wednesday, January 23, 2019, 1:00--2:30 pm
Module 2: univariate analysis
working directories and workspaces
data frames
summarizing continuous data
factors
counts and percents
univariate hypothesis tests

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  Heeren TC, Milton JN. Basic Statistical Analysis Using the R Statistical Package. Boston, MA: Boston University School of Public Health; 2016.
  Chapter 1 and Subsection 2.2.1
  Machlis S. Beginner’s guide to R. Computerworld. August 18, 2017.
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Select section Wednesday, January 23, 2019, 2:30--3:30 pm

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Wednesday, January 23, 2019, 2:30--3:30 pm
Module 2 Lab
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Select section Wednesday, January 30, 2019, 1:00--2:30 pm

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Wednesday, January 30, 2019, 1:00--2:30 pm
Module 3: bivariate and multivariate analysis

continuous vs continuous
continuous vs categorical
categorical vs categorical
introduction to ggplot2
linear regression

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  Heeren TC, Milton JN. Basic Statistical Analysis Using the R Statistical Package. Boston, MA: Boston University School of Public Health; 2016.
  
  Subsection 4.1.1, Subsection 2.2.2, Section 2.5, Section 2.6, and Subsection 4.1.3
  
  Kabacoff R. Data Visualization with R. rkabacoff.github.io; 2018.
  
  Chapter 1 through Chapter 4
  
  Grolemund G, Wickham H. R for Data Science. r4ds.had.co.nz; 2018.
  
  Chapter 3
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Wednesday, January 30, 2019, 2:30--3:30 pm
Module 3 Lab
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Select section Wednesday, February 6, 2019, 1:00--2:30 pm

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Wednesday, February 6, 2019, 1:00--2:30 pm
Module 4: data manipulation

logical objects
missing values
categorization
indexing
subset()
indexing and assignment
ifelse()

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  Aragón TJ. Population Health Data Science with R. bookdown.org; 2018.
  
  Section 4.8, Subsection 2.2.4, Subsection 2.2.5, Section 4.4, Subsection 4.5.6, and Section 4.9
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Lab
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Wednesday, February 13, 2019, 1:00--2:30 pm
Module 5: advanced data manipulation

date objects
rbind() and cbind()
importing other data files
merging data
reshaping data

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  Aragón TJ. Population Health Data Science with R. bookdown.org; 2018.
  
  Subsection 4.1.2 and Section 4.6
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Select section Wednesday, February 13, 2019, 2:30--3:30 pm

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Wednesday, February 13, 2019, 2:30--3:30 pm
Lab

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Select section Wednesday, February 20, 2019, 1:00--2:30 pm

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Wednesday, February 20, 2019, 1:00--2:30 pm
Module 6: programming

if()
functions
the apply functions
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  Aragón TJ. Population Health Data Science with R. bookdown.org; 2018.
  
  Chapter 5, Subsection 3.2.6, Section 3.1, and Section 4.11
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Select section Wednesday, February 20, 2019, 2:30--3:30 pm

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Wednesday, February 20, 2019, 2:30--3:30 pm
Lab

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Select section Wednesday, February 27, 2019, 1:00--2:30 pm

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Wednesday, February 27, 2019, 1:00--2:30 pm
Module 7: R Markdown
R Markdown

Location: Rock Hall 102
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  Xie Y, Allaire JJ, Grolemund G. R Markdown: The Definitive Guide. bookdown.org; 2018.
  
  Chapter 1
  
  Chapter 2 (you may consider skipping 2.7)
  
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  Grolemund G, Wickham H. R for Data Science. r4ds.had.co.nz; 2018.
  
  Chapter 12
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Lab

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