|Introduction to Biostatistics||
Biostatistics and Epidemiology
pdf version of syllabus, 6 pp)
Rosner, B . Fundamentals of Biostatistics,
Sixth Edition, 2006
This course is the first in a two semester sequence (PubHlth 540 and PubHlth 640) of introductory biostatistics. The focus in this first course is statistical literacy. The course begins with a review of the concepts of natural variation. From this perspective, the course is an introduction to biostatistical tools for assessing the distinction between systematic and random variability. Topics include: graphical and numerical description, random sampling and selected probability models (the Bernoulli, binomial, and normal), sampling distributions, confidence interval estimation, and the basics of statistical hypothesis testing. If time permits, there will also be an introduction to simple linear regression and correlation.
Course Objectives and Outcome Competencies
Course Objectives: By the end of this course, you should be able to perform, interpret, and communicate the findings of selected simple statistical analyses of biological and health data, including description, confidence interval estimation and hypothesis testing.
The specific outcome competencies include, but are not limited to the following:
1. The selection and conduct of appropriate statistical analysis – Upon completion of this course, you will have learned the basics of choosing from among the various statistical methods when you want to summarize data, estimate population parameters, or perform a statistical hypothesis test. Specifically, you will have practice in these techniques in the one and two population settings under the assumption of either a normal or binomial population distribution sampling.
2. Integrating analysis strategies in biostatistics with principles and issues in epidemiology – You will have an understanding of the applicability of data description, estimation and hypothesis testing to epidemiology and, specifically, their interpretation with respect to confounding, effect modification, and bias.
3. Evaluation of basic statistical principles in published public health research – At the end of this course, you will have had practice in reading published examples of biostatistics. You will be encouraged to earn your 10% participation grade by selecting a published article from your own particular area of interest and writing a brief summary of its content.
4. Appreciating a conceptual framework that integrates techniques and methods in biostatistics – In this course, two conceptual frameworks are utilized. The first is the perspective that the principles and methods of epidemiologic research are an extension of the scientific method (and the goal of causal inference) to observational studies (and the challenges to causal inference that arise there!). The second conceptual framework is the idea that a statistical hypothesis test is a comparison of “signal” to “noise”.
This course has 9 units (navigation bar, left)
Exam ---- Posting -------------------- Due --------------------Units Covered
Note - There will be no examination of unit 9 (Regression and Correlation).
Note – If you find that you are not able to complete an assignment by the scheduled due
----------------------------------------------------------------------- Percent of Course Grade
Full credit for class participation can be obtained by any one of the following:
Make-up and Rescheduling Policies
• I cannot promise to be able to provide all lecture notes and overheads ahead of schedule; sorry.
• If you miss a class, you can obtain the lecture notes from the course website ( http://www-unix.oit.umass.edu/~biep540w
• Note to Worcester section: As a policy, unless there are extenuating circumstances, Linda Hollis will not mail out lecture notes and overheads.
Letter Grade Determination:
A ------ 95 and over
Important Dates to Remember
• First Class:
• Last Day to Drop with no record – Monday September 15, 2008
Schedule of Lectures and Examinations
ADA Accommodation Policy
Carol Bigelow, PhD
Policy on Academic Dishonesty:
a) Cheating – intentional
deceit, trickery, or breach of confidence, used to gain some unfair
or dishonest advantage in one’s academic work.
Visit the University of Massachusetts Website for its Policy on Academic Dishonesty.
2007 University of Massachusetts, Amherst.
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Page updated: August 25, 2008