BE 540
Introduction to Biostatistics
Biostatistics and Epidemiology
UMass Amherst
Welcome
This Week
Syllabus
Lectures
Demonstrations
Assignments
Resources

Table of Contents

Summarizing Data
Introduction to Probability
Populations and Samples

Bernoulli and Binomal Distributions
Normal Distribution
Estimation
Hypothesis Testing
Chi Square Tests
Correlation/Regression

Syllabus

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(Download pdf version of syllabus, 6 pp)


Instructor:
Instructor: Carol Bigelow, PhD
School of Public Health
402 Arnold House
University of Massachusetts
Amherst, MA 01003
tel: 413/545-1319
email: cbigelow@schoolph.umass.edu


Text:

Rosner, B . Fundamentals of Biostatistics, Sixth Edition, 2006
Duxbury Press.
ISBN 0-534-418201 (Hardcover)

Statistical Software:

None is required and none is needed for completion of the examinations.
It is strongly recommended that you do NOT purchase any statistical software during the first few weeks of the course. Later, if you like, you might consider using a free-ware application (such as StatGraphics) or a rental of Minitab or SAS (if it is available at your work place) or STATA (if it is available at your workplace).


Course Description

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.

 

Outcome Competencies:

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”.


Office Hours:
4:00-5:00 Mondays, in the hospital cafeteria, or,
by appointment.

This course has 9 units (navigation bar, left)
1.  Summarizing Data
2.   Introduction to Probability
3.   Populations and Samples
4. The Bernoulli and Binomial Distributions
5. The Normal Distribution
6. Estimation
7. Hypothesis Testing
8. Chi Square Tests
9. Regression and Correlation

For each unit, the following are provided
Lecture Notes 
Practice Problems with Solutions (Grading is Pass/Fail and is based on timely completion) 
Computer Illustration(s) 
On-line Threaded Discussion (ONLINE section only)
Additional Resources
               A.  Readings
               B.  Other Links of Interest
              


Examination Schedule

Exam ---- Posting -------------------- Due --------------------Units Covered
1 ---------- Mon Oct 13, 2008 -------Mon Oct 27, 2008 ---- 1, 2, 3
2 ---------- Mon Nov 10, 2008 ------Mon Nov 24, 2008 --- 4, 5
3 ---------- Fri Dec 5, 2008 ---------- Fri Dec 19, 2008 ------ 6,7,8

Note - There will be no examination of unit 9 (Regression and Correlation).



Grading Policy:

Your course grade will be based on completion of the practice problems, course participation and three “take home” open book examinations.


Policy on Late Submissions of Practice Problems and Examinations


On time submissions ---------------- full credit for points scored
1-7 days late
---------------------------credit = point score - (20 points)
8-14 days late ------------------------- credit = point score - (40 points)

15+ days late --------------------------zero credit

Note – If you find that you are not able to complete an assignment by the scheduled due
date, I encourage you to use the full week for its completion since the forfeited points
are calculated per week, not per day.

----------------------------------------------------------------------- Percent of Course Grade

1 Submission of practice problems ----------------------------------------- 15%.
2 Examination I
---------------------------------------------------------------- 25%
3 Examination II --------------------------------------------------------------- 25%
4 Examination III -------------------------------------------------------------- 25%
5 Class Participation
---------------------------------------------------------- 10%

Full credit for class participation can be obtained by any one of the following:

(1) submission of SAS or STATA or
SPSS or R illustration; OR

(2) submission of an article and a 1 page
review; OR

(3) 10 corrections to lecture notes, apart
from spelling corrections.


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
A- ----- 90 - 94
B+ ---- 87 - 89
B ------ 83 – 86
B- ----- 80 - 82
C+ ---- 77 – 79
C ------ 70 – 76
F ------ Below 70

Important Dates to Remember

First Class:
On-line Section: Week of Monday September 1-5, 2008
UMass/Worcester Section: Monday September 7, 2008

Last Day to Drop with no record – Monday September 15, 2008

Holiday, Columbus Day – Monday October 13, 2008
• Monday Worcester Class will be held on Tuesday – Tuesday October 14, 2008

Last Day to Drop with “DR” – Tuesday October 14, 2008

Last Class
On-line Section: Week of Monday December 8-12, 2008
UMass/Worcester Section: Monday December 8, 2008


Take Home Final Exam Due – Friday December 19, 2008

 

Schedule of Lectures and Examinations
Week ----Date -----------------------Unit - Lecture --------------------------------------------------Examination
1 ----------Sep 1-5, 2008 -----------Welcome
--------------------------------------------Course Introduction
2 ----------Sep 8-12, 2008--------- 1 – Summarizing Data
3---------- Sep 15-19, 2008 -------1
– Summarizing Data
4 ----------Sep 22-26, 2008 -------2 – Introduction to Probability
5-----------Sep 29-Oct 3, 2008 ---2 – Introduction to Probability
6 ----------Oct 6-10, 2008 ----------3 – Populations and Samples
7 ----------Oct 13-17, 2008 --------4 – Bernoulli and Binomial Distributions -------------Mon Oct 13 – EXAM I posted
8 ----------Oct 20-24, 2008 --------5 – Normal Distribution
9 ----------Oct 27 - 31, 2008 ------5 – Normal Distribution ------------------------------------Mon Oct 27 – EXAM I due
10 --------Nov 3-7, 2008 ----------6 – Estimation
11 --------Nov 10-14, 2008 ------6 – Estimation -------------------------------------------------
Mon Nov 10 – EXAM II posted
12 --------Nov 17-21, 2008 ------7 – Hypothesis Testing
13 --------Nov 24-28, 2008 ------7 – Hypothesis Testing -------------------------------------
Mon Nov 24 – EXAM II due
14 --------Dec 1-5, 2008 ----------8- Chi Square Tests -----------------------------------------
Fri Dec 5 – EXAM III posted
15 --------Dec 8-12, 2008 --------9 – Regression and Correlation
-
-----------Dec 15-19, 2008 ------Course Closeout ----------------------------------------------Fri Dec 19 – EXAM III due

 


ADA Accommodation Policy
Any student who, because of a disability, may require special arrangements in order to meet course requirements should contact me as soon as possible to make necessary arrangements.

Carol Bigelow, PhD
tel: 413/545-1319
fax: 413/545-1645
email: cbigelow@schoolph.umass.edu

Policy on Academic Dishonesty:
The University of Massachusetts/Amherst Senate Document 89-026 defines academic dishonesty as including but not limited to:

a) Cheating – intentional deceit, trickery, or breach of confidence, used to gain some unfair or dishonest advantage in one’s academic work.
b) Fabrication – intentional falsification or invention of any information or citation in any academic exercise.
c) Facilitating dishonesty – knowingly helping or attempting to help someone else commit an act of academic dishonesty.
d) Plagiarism – knowingly representing the words or ideas of another as one’s own work in any academic exercise.
e) Submitting in whole or in part, without citation, prewritten term papers of another or the research of another (including but not limited to such materials sold or distributed commercially).

 

Visit the University of Massachusetts Website for its Policy on Academic Dishonesty.

 

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University of Massachusetts at Amherst
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This is the course web site for BIOEPI 540W, Biostatistics and Epidemiology.
Produced and maintained by the School of Public Health and Health Sciences.
Send comments or questions about this web site to cbigelow@schoolph.umass.edu.
Page updated: August 25, 2008