Biostatistics (biol 467)

 

 

 

 

 


syllabus

Grades (1 April 2018)
 

 



week 1 (Jan 16, 18)
  - installing R and RStudio
  - topic 1: language of experiments (experimental variables, treatments, replication, etc.)
  - assignment 1: language of experiments

week 2 (Jan 23, 25)
  - topic 2: how to structure datasets
  - assignment 2: how to structure datasets & import them into R

week 3 & 4 (Jan 30, Feb 1, 6, 8)
  - topic 3: mathematical variable types AND summarizing data
  - assignment 3_part1: summarizing data in R
  - assignment 3_part2: why you need a statistics program
  - assignment 4: intro to inference via confidence intervals

weeks 5 & 6 (Feb 13, 15)
  - discuss assignment 4 as an intro to inference
  - exam1 (Feb 15 or 16) -- study guide

week 7 (Feb 27, Mar 1) 
  - review exam 1
  - topic 4: principles of inference: sample vs. statistical population


week 8 (Mar 6, 8)
: spring break
  - topic 5: experiments with one continuous RV and one categorical EV
  - assignment 5: two-sample t-test and single factor ANOVA
       (answers to assignment 5)
  - assignment 5-2: single factor ANOVA and unplanned comparisons
       (answers to assignment 5-2)

week 9 (Mar 13, 15) 
  - discuss topic 5 in context of assignment 5 & 5-2 
  - assignment 5-3:  hand calculating t-test and single factor ANOVA

week 10 (Mar 20, 22)
  - discuss topic 5 in context of assignment 5 & 5-2 

week 11 (Mar 27):
  - exam 2  (study guide)

week 12 (Apr 3, 5)
  - Topics 6 and 7: experiments with two continuous variables or two ordinal variables or one continuous EV and one continuous RV
  - assignment 6: correlation and simple linear regression
      (**answers to assignment 6**)
  - assignment 6-2

week 13 (Apr 10, 12)
  - Topics 6 and 7 (continued)
  - Topic 11: experiments with one continuous RV and more than one continuous EVs
  - Topic 8: experiments with one continuous RV and at least two categorical, crossed EVs
  - **assignment 7: factorial analysis of variance**

week 14 (Apr 17, 19)
  - Topic 11 (continued)
  - Topic 15: example of a multivariatae data reduction technique
  - Discuss Assignment 7 and Assignment 8
  - Topic 9: issues that must be considered with block designs and nested designs
  - Topic 10: experiments with one continuous RV, at least one categorical EV, and a continuous EV (a covariate)

week 15 (Apr 24, 26)
  - Topic 12: alternatives when response variable’s error distribution doesn’t meet requirements of a test
  - Topic 13: experiments with one categorical RV and one continuous or categorical EV 

week 16 (May 1, 3)
  - Topic 14: experiments with only categorical variables: analysis of frequencies (i.e., counts) & relative frequencies (i.e., proportions) 
  - exam 3

week 17 (May 8)final exam at 12pm

 

   
   
   
  My "go-to" websites for R
   
 

1. The official R website
https://cran.r-project.org

2. A great overview of R websites, & an excellent reference site itself
http://www.inside-r.org/r-resources-web

3. My FAVORITE quick reference sites
Rstudio Cheat Sheets (https://www.rstudio.com/resources/cheatsheets)
Quick-R (http://www.statmethods.net)
R Tutorial (http://www.r-tutor.com)
R Cookbook (http://www.cookbook-r.com

4. My favorite sites with more detailed explanations and examples
http://whitlockschluter.zoology.ubc.ca/r-code
http://www.ats.ucla.edu/stat
http://rtutorialseries.blogspot.com
http://r4stats.com
http://ww2.coastal.edu/kingw/statistics/R-tutorials/index.html
http://www.gardenersown.co.uk/Education/Lectures/R/index.htm
http://personality-project.org/r/r.guide.html
http://www.burns-stat.com/documents/tutorials/impatient-r
http://www.burns-stat.com/favorite-pages
http://data.princeton.edu/R/default.html
http://manuals.bioinformatics.ucr.edu/home/programming-in-r

5. Three of my favorite "R Community" type sites. Careful, many people will be mean if you ask something that is easily searchable on the site.
http://www.r-bloggers.com
http://stackoverflow.com/tags/r
http://r.789695.n4.nabble.com
 

 
   
 




W&S code for combined stripchart & mean with ci
W&S code for combined stripchart & mean +/- sd customized to assign 2


#creates a new variable (idweek) in the dataset dat1 by combining id with week and making sure there's no space between the value of id and the value of week.
dat1$idweek = paste(dat1$id, dat1$week, sep="")

currentdataframeName$varName<-ifelse((currentdataframeName$varName=="currentTxtValue"), "newTxtValueIfTrue", "newTxtValueIfFalse")

newdataframeName<-subset(existingDataframeName, VarOfInterest=="txtValueOfInterest")