Tuesdays and Thursdays, 11 a.m.-12:15 p.m.
127 Memorial Hall
Instructor: John McDonald
322 Wolf Hall (office)
E-mail: mcdonald@udel.edu
Class web page: http://udel.edu/~mcdonald/statsyllabus.html
Date | Day | Lecture topic | Homework due | |
Aug. 29 | Tuesday |
Introduction; Steps in analysis |
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Aug. 31 | Thursday | Kinds of biological variables | ||
Sept. 5 | Tuesday |
More on kinds of variables; Probability |
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Sept. 7 | Thursday |
Hypothesis testing and alternate schools of statistics
; Exact test of goodness-of-fit |
Homework 1: Collect balance time data (worth three points) | |
Sept. 12 | Tuesday | Power analysis | ||
Sept. 14 | Thursday |
Chi-square test and G-test of goodness-of-fit; |
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Sept. 19 | Tuesday | Chi-square test, G-test and Fisher's exact test of independence; |
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Sept. 21 | Thursday | Cochran-Mantel-Haenszel test | Homework 2: Tests of goodness-of-fit and independence | |
Sept. 26 | Tuesday | Using spreadsheets for statistics | ||
Sept. 28 | Thursday | First exam; see the study guide and the answers | ||
Oct. 3 | Tuesday | Descriptive statistics: Central tendency | ||
Oct. 5 | Thursday |
Descriptive statistics: dispersion, standard error and confidence limits Graphs and tables |
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Oct. 10 | Tuesday |
One-sample and two-sample t-tests |
Homework 3: Descriptive statistics and graphs; survey error bars in papers | |
Oct. 12 | Thursday |
Parametric assumptions: Normality, homoscedasticity, and independence; Data transformations |
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Oct. 17 | Tuesday |
One-way anova: testing homogeneity of means |
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Oct. 19 | Thursday |
One-way anova: post-hoc tests and partitioning variance |
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Oct. 24 | Tuesday | Welch's anova; Kruskal-Wallis test |
Homework 4: Testing assumptions, transformation, one-way anova | |
Oct. 26 | Thursday | Second exam (see the study guide) | ||
Oct. 31 | Tuesday | Nested anova | ||
Nov. 2 | Thursday |
Two-way anova; Paired t-test |
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Nov. 7 | Tuesday | Linear regression and correlation | Homework 5: Nested and two-way anova | |
Nov. 9 | Thursday | Linear regression and correlation, continued | ||
Nov. 14 | Tuesday |
Spearman rank correlation; Curvilinear regression Analysis of covariance |
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Nov. 16 | Thursday | Multiple linear regression | Homework 6: Regression | |
Nov. 21 | Tuesday | Thanksgiving break--no class | ||
Nov. 23 | Thursday | Thanksgiving break--no class | ||
Nov. 28 | Thursday | More on multiple linear regression | ||
Nov. 30 | Tuesday |
Simple logistic regression; Multiple logistic regression |
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Dec. 5 | Tuesday | Multiple comparisons | Homework 7: Survey of statistical tests in your field; write exam questions | |
Dec. 7 | Thursday | Meta-analysis | ||
Dec. 12 | Tuesday | Final exam | See the practice exams |
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 and present 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 biologists use most often.
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.
I do not have fixed office hours, but I will be glad to talk with you outside of class. 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.
We will use an online textbook, Handbook of Biological Statistics. I designed it 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 print the entire book yourself, there is a free pdf, or you can buy the spiral-bound, printed version of the 300-page book for $18 plus shipping.
Attendance is not mandatory, and I will not grade you 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 exam study guides 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 (you can slide it under my office door, 322 Wolf, if I'm not there). Unless an assignment specifically requires it, do not e-mail me your homework assignments; I will not grade them. You must give me your homework assignments on paper.
I try to make the class as interactive as possible, as I find standard lectures to be rather boring. I will therefore call on each of you many times during the semester, whether or not you raise your hand. If this makes you uncomfortable, I can assure you that it would have terrified me when I was in college. Many students have reported on their evaluation forms that being forced to participate kept them attentive in the class and gave them good experience in speaking out. If you do not know the answer to a question, say "I don't know"; sometimes, that's the answer I'm looking for, and even if it's not, I'll try to go to someone else quickly.
I have found that the use of computers during class is distracting for both the students using them and those sitting nearby. You may not use laptops, tablets, smartphones, or other electronic devices during lectures. If I see you using such devices, I'll assume you're looking at porn and mock you accordingly.
I will determine your grade based on the following:
15% First exam
25% Second exam
45% Final exam
15% Homework assignments
I will not curve the grades, because that would discourage you from helping your classmates learn the material; when grades are curved, you get a better grade when your classmates do worse. I will combine the points from the exams and homeworks and convert the total 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.
If you are less than 3 points below the minimum grade needed you need for your program (such as an undergraduate biology major with 67 to 69.9 points, or a biology grad student with 80 to 82.9 points), I will give you the opportunity to take an Incomplete grade and complete an extra credit project. This project will be a lot of work! Once you complete the project to my satisfaction, 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.
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 will be allowed to use a dictionary.
There are seven homework assignments. They will be available on the class web page a couple of weeks before they are due.
The homework assignments make up a relatively small portion of your grade, and they will be loosely graded; if you follow the instructions and 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.
I encourage you to work together with classmates on the homework assignments, if that helps you learn the techniques. However, you must do your own work: analyze the data, draw the graphs, and write the explantations yourself. If you copy material from another student, both you and the student you copied from will get a zero for the assignment.
We are going to use spreadsheets for 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. As a UD student, you can download Microsoft Office, which includes Excel, for free from UDeploy. The spreadsheets should also work with Calc, part of the free OpenOffice.org suite of programs.
I like using spreadsheets for statistics because most of you already know how to use them, and because they make it easy to combine graphics with the statistical tests. 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 spreadsheets 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 also includes 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 spreadsheets. In previous years I have taught SAS as part of this class, but I am no longer going to do this. If you ever need to perform a statistical test for your own research that isn't available in a spreadsheet or web page, let me know and I'll help you do the test with SAS.
If you already know a comprehensive statistical program, such as SAS, JMP, R, SPSS, or Stata, you may use it on the homework assignments instead of my spreadsheets. However, SAS is the only one I know, so I won't be able to help you with any of the others.