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The syllabus for the Statistics for the Life Sciences course (Stat 2480) offered at The Ohio State University. The syllabus includes information about the instructor, course description, goals, objectives, required text, software, website, meeting times, homework, exams, grading scale, and academic misconduct. It also includes information about special accommodations and drop dates.
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Syllabus for Stat 2480: Statistics for the Life Sciences
Instructor: Office: Office Hours: Office Phone: E-mail: Course meeting times and locations:
Required Text: The Analysis of Biological Data, by M. C. Whitlock and D. Schluter, Roberts & Co.,
Software: We will use the R Statistical Software environment for this course. This software is installed in the lab classroom, as well as in most computer labs on campus. It is free software that you can download and install on your personal machines as well ( http://www.r-project.org/). Your TA will help you learn to use R for statistical analysis during lab, but you should also expect to put in time outside of lab doing data analysis with R for homework.
Website: Please visit http://www.carmen.osu.edu/. Check Carmen periodically for announcements about the class and other class material.
Course Description: Statistical methods play an important role in the analysis of data collected in the biological sciences. This course will provide an introduction to the analysis of biological data in a statisti- cal framework. The topics covered include the definition of probability and manipulation of probabilistic quantities; the common discrete and continuous distributions used in modeling biological phenomena; ex- perimental design; and statistical methods for testing hypotheses.
Course Goals: This course satisfies the learning goals of the GEC Data Analysis requirement. In par- ticular, in Statistics 2480 students are expected to understand statistics and probability, comprehend mathematical methods needed to analyze statistical arguments, and recognize the importance of statistical ideas. These goals will be achieved by detailed study utilizing example data from the life sciences.
Course Objectives:
Final Grade: Your final course grade will be based on the following weighting of assessment components: Homework – 25% Exams 1 and 2 – 20% each Lab – 10% Final Exam – 25%
Grading Scale: Grades will be assigned according to the scale below, with course components weighted as listed above. Please note that 25% of your course grade is based on homework assignments. This means that if you fail to turn in any of the homework assignments, the highest course grade you could receive is 75%.
92-100 = A 90-92 = A- 88-90 = B+ 82-88 = B 80-82 = B- 78-80 = C+ 72-78 = C 70-72 = C- 68-70 = D+ 60-68 =D < 60 = E
Academic Misconduct: It is the responsibility of the Committee on Academic Misconduct to inves- tigate or establish procedures for the investigation of all reported cases of student academic miscon- duct. The term “academic misconduct” includes all forms of student academic misconduct wherever committed; illustrated by, but not limited to, cases of plagiarism and dishonest practices in connec- tion with examinations. Instructors shall report all instances of alleged academic misconduct to the committee (Faculty Rule 3335-5- 487). For additional information, see the Code of Student Conduct (http://studentaffairs.osu.edu/info for students/csc.asp).
In particular, please note that although students are often encouraged to work together on homework assignments, all students must submit their own written work IN THEIR OWN WORDS.
E-mail Correspondence: In order to protect your privacy, all course e-mail correspondence must be done through a valid OSU name.nn account. If you have not activated your OSU email account, you can activate your account at https://acctmgt.service.ohio-state.edu/cgi-bin/KRB1EntryAdd.
Drop dates: TBA
Tentative Lecture and Lab Schedule
Lecture No./Lab Date Topic Textbook Readings 1 1/7/13 Introduction, methods for Ch. 1 displaying data 2 1/9/13 Descriptive statistics Ch. 2 and 3 Lab 1 1/11/13 Lab Exercise 1: Intro to R
3 1/14/13 Probability 5.1-5. 4 1/16/13 Probability 5.1-5. Lab 2 1/18/13 Lab Exercise 2: Random Sampling HW #1 Due
1/21/13 No class - Martin Luther King Day 5 1/23/13 Bayes Theorem 5.7 - 5. Lab 3 1/25/13 Problem Solving HW #2 Due
6 1/28/12 Probability distributions 5. 7 1/30/13 Binomial distribution 7.1-7. Lab 4 2/1/13 Lab Exercise 3: The Binomial Distribution HW #3 Due
8 2/4/13 Testing a proportion 7.1-7. 9 2/6/13 Discrete data, χ^2 test 8.1-8. Lab 5 2/8/13 Lab Exercise 4: Confidence Intervals HW #4 Due
10 2/11/13 Poisson distribution 8. 11 2/13/13 Review for Exam # Lab 6 2/15/13 Problem Solving HW # 5 Due
12 2/18/13 Exam #1 Ch. 1- 13 2/20/13 Odds Ratios 9.1-9. Lab 7 2/22/13 Return Exams
14 2/25/13 Contingency tables 9.3-9. 15 2/27/13 Normal distribution 10.1-10. Lab 8 3/1/13 Lab Exercise 5: Normal Probability Plots HW # 6 Due
16 3/4/13 Sampling distributions 10. 17 3/6/13 Estimating means, confidence intervals 11.1-11. Lab 9 3/8/13 Lab Exercise 6: Central Limit Theorem HW # 7 Due
