BISC 643, Biological Data Analysis, Fall 2008

Section 010

Tuesdays and Thursdays, 11 a.m.-12:15 p.m.

116 Gore Hall

Instructor: John McDonald
322 Wolf Hall (office)
E-mail: mcdonald@udel.edu
Phone: 831-2007 (I rarely check messages, so e-mail is better)
Class web page: http://udel.edu/~mcdonald/statsyllabus.html


Note: Those homework assignments that are not in their final version are shown in italics; don't start working on a homework assignment until the final version is posted, as indicated by regular type. Study guides in italics may also be revised, so don't print them out until their link is in regular type.

Date Day Lecture topic Homework due
Sept. 4 Thursday Introduction;
Kinds of biological data
 
Sept. 9 Tuesday Probability  
Sept. 11 Thursday Hypothesis testing;
Exact binomial test
HW 1
Sept. 16 Tuesday Power analysis;
Random sampling
 
Sept. 18 Thursday Chi-square test,
G-test
and Randomization tests for goodness-of-fit
HW 2
Sept. 23 Tuesday Chi-square test,
G-test
and Fisher's exact test of independence
 
Sept. 25 Thursday Small numbers in chi-square and G-tests;
Repeated G-tests of goodness-of-fit
HW 3
Sept. 30 Tuesday Review for the exam  
Oct. 2 Thursday First exam (see the study guide)  
Oct. 7 Tuesday Go over exam answers;
Descriptive statistics: Central tendency
 
Oct. 9 Thursday Descriptive statistics: dispersion,
standard error and
confidence limits
No homework due
Oct. 14 Tuesday Student's t-test;
Introduction to anova;
Single-classification anova: Model I vs. Model II;
testing homogeneity of means
 
Oct. 16 Thursday Planned comparisons among means;
unplanned comparisons among means;
estimating added variance components.
HW 4
Oct. 21 Tuesday Assumptions of anova:
Normality;
homoscedasticity
 
Oct. 23 Thursday Data transformations;
Kruskal–Wallis test
HW 5
Oct. 28 Tuesday Nested anova  
Oct. 30 Thursday Two-way anova;
paired t-test
HW 6
Nov. 4 Tuesday Election Day--no class  
Nov. 6 Thursday Wilcoxon signed-rank test;
sign test
HW 7
Nov. 11 Tuesday Second midterm (see the study guide)  
Nov. 13 Thursday Linear regression;
correlation
 
Nov. 18 Tuesday Spearman rank correlation
Polynomial regression
 
Nov. 20 Thursday Analysis of covariance HW 8
Nov. 25 Tuesday Multiple regression  
Nov. 27 Thursday Thanksgiving, no class  
Dec. 2 Tuesday Logistic regression  
Dec. 4 Thursday Multiple comparisons HW 9
Dec. 9 Tuesday Meta-analysis  
Dec. 4 Thursday Review for exam  
Dec. ?? ?? Final exam (see the study guide
and the practice questions
and the second set of practice questions.)
 

Purpose of the course

This course is designed for biologists who want to apply appropriate statistical tests to their data, and who want to understand the statistical tests that other biologists have used. We will therefore spend little time on the mathematical basis of the statistical tests, focusing instead on how to choose the appropriate test for a given data set, how to design experiments to make them more suitable for statistical analysis, and how to interpret the results of statistical tests. While it would be impossible to cover every statistical test ever used by biologists in a single course, we will cover many of those techniques that are commonly used.

At the end of the course, you should be able to determine the correct statistical technique to apply to many biological experiments, and you should be able to apply each technique and interpret the results. You should also be able to recognize experimental designs for which you have not learned the appropriate statistical test, and you should be able to ask intelligent questions when consulting with a statistician about such experiments.

Office hours

There are no fixed office hours. You can make an appointment by talking to me before or after class or by e-mailing me. If you have questions while studying or doing the homework assignments, feel free to e-mail me or drop by my office.

Textbook

We will use an online textbook, Handbook of Biological Statistics. It is designed for online use, but if you want to print individual pages, they are formatted to print well (with most of the extra junk, like the sidebar and banner, omitted to save space). If you want to have a printed copy of the whole handbook, you can buy one from Lulu.com for $16 plus shipping.

Attendance

Attendance is not mandatory, and you will not be graded on your in-class participation. However, I think it will be a lot easier to learn the material if you attend class. Homework assignments and class handouts will be available from the class web page (http://udel.edu/~mcdonald/statsyllabus.html). If you are absent when a homework assignment is due, please try to turn in the assignment before the next class. Do not e-mail me your homework assignments.

Grading

Your grade will be based on the following:

15% First midterm exam
30% Second midterm exam
40% Final exam
15% Homework assignments

The grades will not be curved. The points from the homework and exams will be combined and converted to letter grades as follows:

A 93-100; A- 90-92.9; B+ 87-89.9; B 83-86.9; B- 80-82.9; C+ 77-79.9; C 73-76.9; C- 70-72.9; D+ 67-69.9; D 63-66.9; D- 60-62.9; F 0-59.9.

Students who are less than 3 points below the minimum grade needed for their program (such as an undergraduate biology major with 67 to 69.9 points, or a biology grad student with 80 to 82.9 points) will be given the opportunity to take an incomplete grade and complete an extra credit project. This project will be a lot of work, such as surveying the statistical tests used in a large set of scientific papers and critiquing their correctness. Upon satisfactory completion of the project, you'll get the minimum grade needed for your program (such as C- for undergraduate biology majors or a B for biology grad students). There will be no other extra credit.

Exams

The exams will be cumulative. The main emphasis of the exams will be testing your knowledge of what the appropriate statistical test is to use in a particular situation and how to interpret the results. You will not be allowed to use reference books or notes during the exams, and you will not need a calculator. If your native language is not English, you may use a dictionary.

Homework assignments

A homework assignment is due on most Thursdays. They will be available on the class web page a couple of weeks before they are due. I will not hand out printed copies of the assignments in class.

The homework assignments make up a relatively small portion of your grade, and they will be loosely graded; if you make a sincere effort on all parts of an assignment, you will probably get full credit. Despite this, I suggest that you put a lot of effort into the homework. Many of the skills I hope you learn from this class can only be learned by doing, not by listening to me talking, so your statistical education will be incomplete (and you will struggle on the exams) if you do not do the homework to the best of your ability. Please drop by my office or e-mail me if you need help on the homework.

Software

We are going to use Excel spreadsheets for most of our data analysis. The web page for almost every statistical test will include a spreadsheet that you can download and use with the Windows or Macintosh versions of Excel. Most of these spreadsheets should also work using the free program Calc, part of the OpenOffice.org suite of programs, although I haven't tested all of them yet.

I like using Excel for statistics because most of you already know how to use it, and because it makes it easy to combine graphics with the statistical test. If you're interested in a field that only uses fairly basic statistics, such as molecular or cell biology, the tests that you can do with Excel are likely to be all you'll ever need.

Wherever possible, I've linked to someone else's web page that will perform each statistical test, and you may use them for the homework if you prefer. I found most of these web pages using John Pezzullo's excellent list of Interactive Statistical Calculation Pages, which is a good place to look for information about tests that are not discussed in this course. For most tests, the web page version is not as easy to use as a spreadsheet, and many web pages only handle limited sample sizes. Some web pages, however, do tests that would be difficult to set up on a spreadsheet.

Each of my web pages about a statistical test will also include instructions for performing the statistical test using SAS. SAS is a powerful but user-unfriendly statistical package that can do statistical analyses that are far beyond the abilities of Excel. While I don't expect you to become an expert in SAS, I'm going to try to teach you some of the basics this fall. Most of the homework assignments will require that you do each statistical test two ways, once with a spreadsheet or web page, then again with SAS. This is the first time I've tried this, and I don't know how well it will work. So see if you can get SAS to give you the same answer as the spreadsheet or web page, but don't spend too much time on it.

If you already know another comprehensive statistical program, such as SPSS or Stata, you may use it on the homework assignments instead of SAS, but don't ask me for help.


Return to John McDonald's home page

This page was last revised September 27, 2008. Its URL is http://udel.edu/~mcdonald/statsyllabus.html