Instructors:

Instructor:	Dr. Jim Novak
Office:	1162 Life Sciences Annex; 581-6385
Office Hours:	MWF: 10:00 – 11:00; Th 14:00 – 15:00 or by appointment
email	jmnovak@eiu.edu

Text: Rosner, Bernard. 2006. Fundamentals of Biostatistics, 6^th Ed.. Thomson Brooks/Cole, Belmont, CA (ISBN 0-534-41820-1)

Class Time: Lecture MW 09:00 – 9:50, Lab TH 09:00 – 10:50

Class Location: Lecture - 1130 Life Sciences Annex, Lab - 1130 Life Sciences Annex

OBJECTIVES:

General:

The course is designed to give the students an introduction to simple analytical techniques for the statistical analysis of biological data. Basic descriptive statistics, graphical data analysis, hypothesis testing of means, regression and simple analysis of variance will be covered. Emphasis will be on assumptions and when to use specific procedures rather than on proofs or statistical theory. Correct use and interpretation of statistical procedures will be emphasized in the laboratory.

Specific:

1.) Develop an understanding of topics such as hypothesis testing, the normal and other distributions, and experimental design as they relate to the analysis of biological data.

2.) Recognize the utility & limitations of the following methods related to biological data: contingency analyses, z & t-tests, ANOVA, means-comparison procedures, linear regression, correlation, and non-parametric analyses.

3.) Develop modern computational skills through using a statistical programming language (SAS) and spreadsheet software (MS EXCEL).

FORMAT

Monday and Wednesday classes will cover specific topics in a traditional lecture/discussion format. Laboratory sessions will not occur every week, during the times when there is no lab scheduled WE WILL STILL HAVE CLASS, but it will be a traditional lecture. Both lecture and laboratory sessions will be held in the computer laboratory and will emphasize the use of SAS© to analyze data using statistical techniques previously discussed in class. Each individual will have access to a computer and the appropriate software during the laboratory class period.

GRADES

You will be evaluated based upon the completion of homework assignments, laboratory exercises, and three section exams. Exams will be open book/notes part of the exam may be take-home and require the use of computational software to complete the exam. The breakdown of credit is as follows:

MISSED EXAMS

If you cannot attend class on the day of an exam or lab, you must notify the instructor at least 24 hours prior to the exam or lab. Exams/labs will only be rescheduled for students that give adequate notification and documentation (as required) of their absence or in extreme cases (sudden illness, family emergency, etc.).

ACADEMIC HONESTY POLICY

I expect that you will never passively or actively cheat on any of my exams, or those administered by your other instructors. Any documented incidence of cheating or plagiarism will result in an automatic failing grade (“F”) for the entire course, and notifications to the Dean’s office and Judicial Affairs. Please feel free to speak with me, or consult your Student Handbook, if you have any questions concerning this matter.

DISABLED STUDENTS

Disabled Students should contact the Office of Disability Services (9^th St.Hall 2002; x6583) for any arrangements that need to be made in order to ensure that you get the most out of this course. Within reason, I am willing to make whatever accommodations are necessary to facilitate your learning of this material.

FURTHER ASSISTANCE

If you suddenly find yourself with a question that is burning a hole in your brain, and cannot reach me, there are several ways of obtaining the answer. Here are some examples:

1. The authors of your text have thoughtfully provided numerous problems for you to practice your statistical skills. The solutions for some of theses are listed in the Answers to Selected Problems section at the end of the book. The companion CD also has additional solutions.

2. Do not be afraid to use the internet. Google is a powerful search engine and can help you find additional information on topics. BE AWARE THAT THE QUALITY OF INFORMATION VARIES GREATLY FROM SITE TO SITE ON THE INTERNET. If the information on the site conflicts with the book you may want to bring this up in class and we can discuss it.

3. Seek help at the Learning Assistance Center (x6696) or the Counseling Center (x3413) to obtain help with studying for this class.

4. Help each other -- get to know your fellow students! Active learning through testing each other on the material is one of the most effective ways to learn where your weaknesses lie with this subject matter.

ASSIGNMENT #1 – due Friday, 13 Jan

Send me an email message (jmnovak@eiu.edu) containing the following items, each on a new line of text:

Your name as you wish to be addressed
Your SSN - if you prefer not to send your SSN via email simply state so.
A version of the following statement: "Yes/No you may/may not post my grade by special code." [If "yes," then provide a 6-digit code -- you may use any sequence of numbers or letters].
your phone #
A version of the following statement: "Yes/No you may/may not release my phone number to the rest of the class."
Your class standing (Freshman, Sophomore, Junior, Senior)
Your major
A version of the following statement: "Yes/No you may/may not release my email address to the rest of the class."

LECTURE AND LABORATORY SCHEDULE

Week				Topic	Reading	Lab Topic
1	9-Jan	-	12-Jan	Class Introduction; Descriptive Statistics	Chap. 1, 2	Lecture
2	18-Jan	-	19-Jan	Probability	Chap. 3	Lecture
3	23-Jan	-	26-Jan	Discrete Probability Distributions	Chap. 4	Simple Statistics and Graphs
4	30-Jan	-	2-Feb	Continuous Probability Distributions; Estimation	Chap.5, 6	Lecture
5	6-Feb	-	9-Feb	One Sample Inference	Chap. 7	Estimation and Inference on a Mean
6	13-Feb	-	16-Feb	Two Sample Inference	Chap. 8	Lecture Test 1
7	20-Feb	-	23-Feb	Correlation Analysis	Chap. 11.7, 11.8, 11.11, 11.12	Inference on Two Means
8	27-Feb	-	2-Mar	Regression Analysis	Chap. 11.1 - 11.6	Lecture
9	6-Mar	-	9-Mar	Regression Analysis	Chap. 11.9 - 11.10, 11.13	Regression
10	13-Mar	-	16-Mar	Spring Break - No Classes
11	20-Mar	-	23-Mar	ANOVA	Chap 12.1 - 12.5	Lecture Test 2
12	27-Mar	-	30-Mar	ANOVA	Chap 12.6 - 12.10	ANOVA
13	3-Apr	-	6-Apr	Categorical Data	Chap. 10	Lecture
14	10-Apr	-	13-Apr	Nonparametric Statistics	Chap. 9	Categorical Data
15	17-Apr	-	20-Apr	TBA	TBA	Lecture
16	24-Apr	-	27-Apr	TBA	TBA	Lecture Test 3

FINAL EXAM – Tuesday, May 2, 0800 - 1000

Note: All dates represent my best guess. However, since this is the first time I have taught this course, without using SAS, all dates should be treated as tentative.