Statistical Inference & Analysis
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| Syllabus | Lecture notes | Study questions | SAS lab |
| Exams | Final project | Grades |
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Course news
The in-class final exam on Saturday, Dec 6th, will be at 10:30 am rather than at 8:00, as announced in the syllabus. The in-class exam will explicitly cover the final third of the course, though of course all material in course is cumulative. To accommondate a number of students who are leaving town early, I will be handing out the take-home exam on the last day of class (Dec 3rd); it will be due at the time of the in-class exam on Saturday. Final projects are due at 5:00 pm on Wednesday, Dec 10th.
It seems that there are conflicts for some people with completing the take-home between Wednesday and Saturday. So, we'll make it optional -- you can either (1) pick up the exam at the end of class on Wednesday morning (Dec 3rd) and turn it in by noon on Monday (Dec 8th), or (2) pick it up after the in-class exam on Saturday morning (Dec 6th) and turn it in by noon on Thursday (Dec 11th). That will give everyone the same amount of time to complete it, and should still give me sufficient time to grade them. Final projects are still due by 5pm on Wednesday (Dec 10th).
My solution to problem 3a (dealing with a Wilcoxon signed-rank test of the Martian data) of the 4th set of practice problems was wrong. The answer has been corrected and the solutions have been reposted.
Watch here for any breaking news or information about the course. If I will be unable to make it to a class because of sickness or other emergency situation, I will send an email message to all students via the TechSIS system, but will also put a notice here.
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Purpose of the course
The purpose of this course is to survey the statistical principles of research design for experimental and observational studies, emphasizing (1) both exploratory and inferential statistics, (2) both parametric and nonparametric statistics, and (3) problems and techniques of particular importance in cellular and organismic biology. The course will require only a basic knowledge of algebra and no prior statistics. The purposes and assumptions of statistical methods will be stressed as much as (and often more than) the mechanics. We will use Minitab and SAS as computer research tools, and the course will require a final project. The basic issues to be treated will include: basic statistical concepts, basic experimental design, tools and strategies of univariate and bivariate data analysis, randomization techniques (e.g., permutation and bootstrapping), and comparisons of the robustness and efficacy of statistical procedures.
Objectives
This course should allow you to develop an understanding of: (1) the ways in which biological hypotheses can be translated into statistical hypotheses, (2) basic concepts of probability and probability distributions and how they are applied to statistical estimation and testing, (3) the logic underlying statistical confidence intervals and hypothesis tests. You should be able to read and understand descriptions of and results from statistical tests in the scientific literature.
Format
This is fundamentally a lecture course, based on the provisional outline but with short tangential subjects pursued at any time as the need arises. Practical experience will be derived on your part from a number of out-of-class assignments, including computer work. In addition, a final written report on a data-analysis project will be required.
Computer lab
The computer laboratory section will meet once or twice per week in Biol 405. We will learn the fundamentals of statistical analysis using the Minitab and SAS software packages. There will be short weekly assignments that will allow you to become facile with the software.
Prerequisites
One semester of college algebra (MATH 1320) or equivalent.
Time and place
10:00 – 10:50 MWF, 106 Biological Sciences
Textbook
Kachigan, S.K. 1986. Statistical Analysis: an interdisciplinary introduction to univariate & multivariate methods. Radius Press, NY. 589 p. ISBN 978-0942154993.
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