Biology 620: Biometry

Professor Mark Butler
Department of Biological Sciences
Old Dominion University

Course Overview

This course is intended as a first course, or perhaps a refresher course, in statistical methods and experimental design for biology graduate students. The focus is on application and hypothesis testing, not theory or exploratory data analyses, with examples drawn from the field of biology. The course begins with a review of the basics of applied statistics (e.g., types of data, descriptive statistics, hypothesis testing) and then covers in rapid succession a series of general univariate statistical techniques most commonly used by practicing biologists. We also cover issues of experimental design in some detail, using relevant biological examples, in-class group exercises, and discussion. The course concludes with a presentation of alternative methods to parametric statistics and an overview of common multivariate techniques. Students interested in careers in research are encouraged to continue their statistical training in more advanced subjects not covered in this course.

Much of the course requires independent work outside the classroom on homework execercises in which students use statistical software to analyze data and interpret those results, after first recognizing the appropriate test and fulfilling the assumptions of the test. An independent project, emphasizing proper experimental design, preliminary sampling, power analysis, and then final analysis of the data (rather than data collection per se) is also required.

"... the main function of that section of statistics that deals with tests of significance is to prevent people from making fools of themselves ... by claiming that their favorite theory is substantiated by observations that do nothing of the sort." - D. Colquhoun (1971), Lectures on Biostatistics




 

 




 


SYLLABUS
BIOL 620: BIOMETRY

 

Instructor:                       Professor Mark Butler

Graduate Assistant:          Thomas Dolan (683-6249; twdolan@verizon.net)

Office/Phone/Email:        MGB Room 302K / 683-3609 / mbutler@odu.edu

Office Hrs:              I prefer to meet by appointment so we can meet when it is most convenient   for both you and me, and so we can meet as long as is necessary.  Email me, call me, or see  me after class about setting up an appointment. 

Text:                             Biostatistical Analysis, 5th Edition, J.H. Zar (required)
                                    SPSS Base User's Guide, SPSS Inc. (recommended)

Class Hrs & Room:  Tuesday and Thursday, 4:20 PM - 6:00 PM; room 352 MGB

Course Objectives

At the conclusion of this course students will understand the essential components of exper¬imental design and will be familiar with the basic statistical techniques most commonly employed in the biological sciences. Students will recognize the assumptions and data requirements for these statistics, and will learn how to analyze and interpret biological data with these techniques. Much of this course requires work outside the classroom. If nothing else, I hope that you will come to appreciate that: "... the main function of that section of statistics that deals with tests of significance is to prevent people from making fools of themselves ... by claiming that their favorite theory is substantiated by observations that do nothing of the sort." 
                                                          - D. Colquhoun (1971), Lectures on Biostatistics

 

Computer Use

We will be using a windows-based statistical program called SPSS to analyze data. SPSS is one of the most widely used and powerful statistical analysis systems for the PC. It is relatively simple and offers lots of on-line help menus, but like any program it takes some getting used to. The SPSS User's Guide manual is a recommended text and available at the bookstore; this and other SPSS manuals are also available in the Reserve section of the Library. I'll also pass out lots of "how to" handouts for specific analyses.Class will also meet from 6:30 - 8:30PM on Jan 16th and 18th in BAL 105-40 for "hands-on" instruction on the basics of the SPSS program; an optional computer help session will also be held on Jan 23rd from 6:30-8:30PM in BAL 105-40.

SPSS is available to you on all of the computers in the University's Computer rooms once you have a university Local Area Network (LAN). Check the university's website for computer room locations and hours of operation (http://occs.odu.edu/labs/locations/).  If you would like to use SPSS at home on your own computer, you can purchase: (a) the less complete but less expensive student version of SPSS, or (b) the complete "Grad Pak" version of SPSS for a bit more from the University Bookstore or Tech Store.  You must have a LAN Account for our SPSS instruction sessions and to use SPSS on university computers.  Obtain a LAN Account ASAP if you do not have one.  Students automatically obtain a LAN account when they activate their MIDAS (Monarch Identification and Authorization System) ID account.  To activate your MIDAS account go to: http://occs.odu.edu/accounts/midas/

Grading

I follow the University's grade scale, so "+" and "-" grades will be assigned. Your final grade will be calculated as follows:

Homework
Independent Project
Midterm Exam
Final Exam

45% (3 @ 15% each)
15%
20%
20%

A Note on Original Work:  A Note on Original Work:     Students in this course may assist each other in learning and operating SPSS, but may not help one another on the homework problems!  Determination of the appropriate statistical procedures as well as data interpretation, writeup, and discussion must be each student's own original work!  I will deal with infractions of these rules in strict accordance with university policy  

Description of Assignments and Exams

Homework: Three homework assignments will be given. In each, students will ascertain the appropriate analysis, analyze the data, and interpret the results. Homework will generally be due 1 week after the assignment is given; tentative assignment and due dates are in the schedule below. The structure of the homework reports should follow that shown for the answers to the practice problem sets, found on the Biometry class website (http://www.odu.edu/~mbutler/biometry%20webpage/index.html).

Late homework: 10% will be deducted from your homework grade for each day late.

Exams: The midterm exam will be open-book and open notes; it will be given during class on Thursday, March 1st. The final exam will be a comprehensive, take-home test similar to the homeworks; you must email or deliver it to me by 5PM on Thursday, April 26th. The exams will not be returned to you, but you will have the opportunity to review them.

Independent Project: You will employ what you learn about experimental design and statistical analyses to design, execute, analyze, and interpret the results of a small experiment that you devise. This must be completed on your own and need not be a biological study. You'll have about two weeks to complete this assignment, which includes both a short paper describing the study and results and an informal oral presentation to the class. I'll give you detailed instructions later. Presentations will be given on Tuesday, April 24th; reports are due in class that day as well.

Reading Assignments & Practice Questions: On the Biometry class website you will find a few scientific papers (pdf files) on experimental design issues and philosophy that I encourage you to read. Practice questions and answers, similar to those assigned for homework, are also available on the Biometry class website:(http://www.odu.edu/~mbutler/biometry%20webpage/index.html).

 

Course Outline & Tentative Schedule 

  Wk

Dates

Topic

Book Chapters

   1

1/9 & 1/11

Types of data & studies, review of descriptive statistics

1 - 4

   2

1/16 & 1/18

Hypothesis testing, 1-sample t-test

Computer Instruction after lecture on 1/16 & 1/18 from 6:30 - 8:30PM in BAL 105-40

7

   3

1/23 & 1/25

Paired t-test, 2-sample t-tests

Optional computer help session after lecture on 1/23 from 6:30 - 8:30PM in BAL 105-40

Homework #1 assigned

8 & 9

   4

1/30 & 2/1 

Evaluating parametric assumptions & data transformations

13

   5

2/6 & 2/8

1-Factor ANOVA
Homework #1 due on 2/8

10

   6

2/13 & 2/15

Multiple comparison tests

Homework #2 assigned

11

   7

2/20 & 2/22

Experimental Design

Homework #2 due on 2/22

 

   8

2/27 & 3/1

Experimental Design

In-class MIDTERM EXAM Thursday 3/1

 

   9

3/6 & 3/8

Spring Break - No Class

 

 

  10

3/13 & 3/15

Randomized-Block & Repeated Measures ANOVA

2-factor ANOVA

12, 14

  11

3/20 & 3/22

Multifactorial ANOVA

14

  12

3/27 & 3/29

Split-plot ANOVA & Nested ANOVA

Homework #3 assigned

15

  13

4/3 & 4/5

Correlation & Regression

Independent Project Planning

Homework #3 due on 4/5

16 - 18

  14

4/10 & 4/12

Correlation & Regression

Analysis of Covariance

12, 17

 

  15

4/17 & 4/19

Categorical Analysis

Take-home final exam assigned

21 - 22

  16

4/24

Independent Project Presentations & Project Report Due

 

 

4/26

TAKE-HOME FINAL EXAM DUE BY 5PM

 

 

Classroom Requirements of the Department of Biological Sciences

 1.      There is to be no consumption of food or drink in the laboratory or lecture rooms. If you require food or drink for medical reasons, please move to the lobby.

 2.      If you are in conflict with a faculty or staff member, your first point of contact is the Biology chairman. The chairman's office is located in room 110 of MGB.

 3.      Inform the instructor of any medical conditions or needs you may have. 

 4.      Turn off electronic devices (cell phones, hand palms, etc.) during the lecture and laboratory periods.

 5.      Read the document "Safety in the Biology Teaching/Research Labs", which is located in each laboratory.   For laboratory courses, fill out and sign the Emergency Information Sheet, which will be provided for you.

 Refer any questions concerning these requirements to the Department of Biological Science Chair,  Lytton John Musselman Room 110 M

 

BIOMETRY HANDOUTS  

 

BIOMETRY EXAMPLE PROBLEM SETS  

  • One-sample t-test  
  • Two-sample t-test  
  • Paired t-test  
  • 1-factor model I ANOVA  
  • 1-factor model II ANOVA  
  • Randomized-block ANOVA  
  • 2-factor model I ANOVA  
  • 2-factor mixed model ANOVA  
  • 2-factor Split-Plot ANOVA  
  • 2-factor Nested ANOVA  
  • 2-factor Repeated-measures ANOVA  
  • Correlation  
  • Regression  
  • Multiple Regression  
  • 2-way Contingincy Table Analysis  
  • 3-way Contingincy Table Analysis

 


 

 

 

 

 


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