Biology 611: Biometry Home Page

"I kid you not, statistics are now the sexiest subject on the planet"
--Hans Rosling, 2010

Course Schedule

Lecture notes

Lecture notes are availible as slides or as pdf documents deposited in this directory. Direct links are below:

Lectures

• Syllabus , Introduction , Introduction to data , Introduction to R
• Descriptive statistics
• Begin probability distributions ; continuous probability distributions
• Comparing data to Poisson distributions
• Hypothesis testing I
• Hypothesis testing II
• Power
• ANOVA I
• ANOVA II
• Experimental design
• non-parametric
• non-parametric cont
• posthoc tests
• ANOVA models (nested)
• Regression
• Regression cont
• Regression cont
• Combining continuous and discrete independent variables
• Fitting distributions
• Homegrown application of ML estimation
• Relaxing some of the assumptions of linear models
• Regression cont
• Assumption of equal variance in groups
• Resampling approaches
• more Resampling approaches
• Analyzing count data
• MultivariateI: Ordination
• MultivariateI: Clustering
• Reproducible research
• Survival

Labs

1. Statapult
2. Intro to R
3. Describe data
4. Probability and pdfs
5. Begin hypothesis testing
6. power
7. intro anova
8. continue anova
9. non-parametric
10. what do you do after ANOVA?
11. nested models
12. intro to regression
13. regression cont.
14. regression cont.
15. Maximum likelihood
16. Maximum likelihood regression
17. Resample
18. glm: logistic regression
19. Frequencies
20. Clustering
21. Multivariate lab
22. Unequal variance

Assignments

During the semester, assignments can be found in this section

Problem sets

• Problem set 1 ; Solutions
• Problem set 2

Exams

• Exam 1 solutions
• Exam 2

Presentation information

• evaluation form

Datasets

Datasets used in class can be found here .

Statpult data

Here is the link to the google doc containing the randomizations for the statapult experiment. Here is the link to the google doc containing the statapult data collected this semester

Source

Scripts used in lecture and lab can be found here

Useful links

This section contains links that you may find useful:

• R homepage
• SimpleR
• StatSoft.com
• CRAN
• Tinn-R , an editor for R code

• JGR (Jaguar) a java-based R frontend (more cross-platform than tinn-r)

• Rosling population growth (hi-tech)

• Rosling on population growth

• Tim Lee on linear regression
• Statistics Jokes I
• Statistics Jokes II

No References!