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BIOSTATS 540 - Fall 2017
Introduction to Biostatistics
Biostatistics and Epidemiology
UMass Amherst
Instructor: Carol Bigelow




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Syllabus

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Unit Lecture Notes


Unit Tests

Illustrations


Other Resources






Course Unit Pages

1. Summarizing Data

2. Data Visualization

3. Probability: Basics

4. Probabilities in Epidemiology

5. Populations and Samples

6. Bernoulli and Binomal Distributions


7. Normal Distribution


8. Statistical Literacy: Estimation and Hypothesis Testing


9. One Sample Inference

10. Two Sample Inference


11. Chi Square Tests


12. Simple Linear Regression and Correlation

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Syllabus

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Download hardcopy of 2017 syllabus here


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



There is NO required Text:

Instead, an optional text by Whitlock and Schluter is offered. It is quite good and comes with nice internet resources:

Resources for optional text
The Analysis of Biological Data, Second Edition
(Student resources)


Other Text Resources for Those Wishing Them (again - not required):

(1) Course content
Whitlock MC and Schluter D
The Analysis of Biological Data, Second Edition
Macmillan Learning
2015
ISBN-10: 1-936221-48-9

(2) A very reader friendly resource, very basic, for those of you dreading this course
Triola MM and Triola MF
Biostatistics for the Biological and Health Sciences
Pearson Addison Wesley
2006
ISBN 0-321-19436-5

(3) R for Beginners
Horton NJ, Pruim R, Kaplan DT
A Student’s Guide to R: Project Mosaic
https://cran.r-project.org/doc/contrib/Horton+Pruim+Kaplan_MOSAIC-StudentGuide.pdf

(4) STATA for Beginners
Institute for Digital Research and Education, UCLA
Resources to Help you Learn and Use Stata
http://www.ats.ucla.edu/stat/stata/

(5) StatKey, for those of you dreading using the computer
Resources to accompany Lock, Lock, Lock, Lock & Lock:  Statistics: Unlocking the Power of Data
http://www.lock5stat.com/StatKey/


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Statistical Software:

First and very importan. This is NOT a course in programming. Instead, I will provide illustrations of statistical software use. With luck,
you can follow along. And, with a bit more luck, you can use these illustrations in future work. But use of any statistical software package will not be needed for any of the exams.  


We will be using statistical software in the homeworks and practice problems.  You have 3 choices, depending on your interest and comfort zone!

#1.  R with RStudio  -  FREE! 
      Choose this if you anticipate  using R elsewhere (work, graduate school)

#2.  Stata version 15 -  Price varies (Cheapest is $45 for 6-month rental)
      Choose this if you anticipate using STATA elsewhere (work, graduate school)

#3.  StatKey – FREE!
       Choose this if you are dreading this course, are dreading using statistical software and if
       you do not anticipate doing statistical programming yourself.

You do NOT need to have obtained any statistical software before the class starts.  I will provide you with complete instructions in the first weeks.




Course Description

This course is the first of a two semester sequence: BIOSTATS 540 - Introductory Biostatistics and BIOSTATS 640 - Intermediate Biostatistics. Minimal mathematical background is required. Familiarity with algebra is generally sufficient. The goal of BIOSTATS 540 is basic statistical literacy. It begins with a discussion of the ideas of variability in nature and the tools we use for its description. The distinctions between systematic versus chance variability are detailed. Concepts in simple random sampling and sampling distributions are introduced. Within this framework, you will learn selected methods of data description, estimation and hypothesis testing.

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.

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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. Explain why we need biostatistics;
2. Distinguish among the different measurement scales and explain why these distinctions matter;
3. Produce basic, numerical, summaries of data;
4. Produce basic, graphical, summaries of data;
5. Explain basic concepts of randomness and probability;
6. Compute and interpret basic statistics computed from 2x2 tables of epidemiological data;
7. Describe selected probability distributions: Uniform, Bernoulli, Binomial, Normal, Student-T, F, and Chi Square;
8. Computer and interpret confidence intervals and hypothesis tests in selected settings: single sample, single sample paired data, and two indpendnet samples;
9. Interpret the results of statistical analyses found in selected, basic, public health studies; and
10. Interpret vital statistics and public health records.


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Office Hours:
This class has two sections: 1) Online using Blackboard Learn; and 2) Face-to-face at the UMass/Medical School campus, Worcester MA.

Online section:
We will respond to Blackboard messages within 24 hours every day except Saturday. I encourage you to take the day off on Saturday, too!
You are also welcome to email me directly at cbigelow@schoolph.umass.edu. Or telephone me at 413-545-1319 (Note - I may not answer on Mondays as this is the day that I am at the Worcester campus, so please leave a message)

Worcester, in-class, section: Mondays 4:00 - 5:00 UMass/Medical School Cafeteria, or by appointment.

This course has 12 units
1, Summarizing Data
2. Data Visualization
3. Probability: Basics
4. Probabilities in Epidemiology
5. Populations and Samples
6. Bernoulli and Binomial Distributions
7. Normal Distribution
8. Statistical Literacy - Introduction to Estimation and Hypothesis Testing
9. One Sample Inference
10. Two Sample Inference
11. Chi Square Tests
12. Simple Linear Regression and Correlation


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Grading Determination and Policy on Late Submissions:

Your course grade will be determined from completion (pass/fail) of participation, homeworks together with your scores on 3 tests, as follows.

Participation - 5%
I will request "participation" from you 5 times (each worth 1% of your grade). Specifically, I will use the Blackboard message utility (not your personal email). You must respond within 3 days to earn participation credit.
Homeworks - 20%
I will post several homeworks. You do not need to do all of them. However, you msut submit 10 homeworks (each worth 2% of your grade)
Test 1 - 25%

Posting Date: Monday September 25, 2017
Due Date: Tuesday October 10, 2017

Topics Covered:
1 - Summarizing Data
2 - Data Visualization

Test 2 - 25%
Posting Date: Monday October 23, 2017
Due Date: Monday November 6, 2017

Topics Covered:
3 - Basic Probability
4 - Probabilities in Epidemiology
5 - Populations and Samples
6 - Bernoulli and Binomial Distributions
7 - Normal Distribution
Test 3 - 25%
Posting Date: Monday November 27, 2017
Due Date: Monday December 18, 2017

Topics Covered:
8 - Statistical Literacy: Introduction to Estimation and Hypothesis Testing
9 - One Sample Estimaation and Hypothesis Testing
10 - Two Sample Estimation and Hypothesis Testing


NOTE - There is NO test of Unit 11 (Chi Square Tests) or Unit 12 (Simple Linear Regression and Correlation)
.

All exams are "take home" exam, open book. You are allowed to used whatever resources you like. But you are NOT allowed to consult with any person except the course instructor.

Policy on Late Submissions

I will accept late submissions upt o one week, with a 20 point penalty. If you know you will be submitting your work late, I encourage you to use the full one week
grace period, as the point deduction is the same!

On Time
Full Credit for points scored
1-7 Days Late
Points scored - 20 points
8+ Days Late
0 points (no credit)

 

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

Test Schedule:

  Posting Date DUE Date
(Last date for submission for credit)
Test #1
Unit 1 - Summarizing Data
Unit 2 - Data Visualizationa
September 25, 2017
Tuesday October 10, 2017
(October 17, 2017)
Test #2
Unit 3 - Basic Probability
Unit 4 - Probabilities in Epidemiology
Unit 5 - Populations and Samples
Unit 6 - Bernoulli and Binomial Distributions
Unit 7 - Normal Distribution
October 23, 2017
Monday November 6, 2017
(November 13, 2017)
Test #3
Unit 8 - Statistical Literacy
Unit 9 - One Sample Inference
Unit 10 - Two Sample Inference
November 27, 2017
Monday December 18, 2017
(December 20, 2017)


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For PHP Online Students - Policy on GPA and Course Repeat:
If you are an MPH or PHP online student, you must earn a grade of "B MINUS" or better in this course.

All students must maintain a 3.0 GPA during their time as students in the program.  In addition, all MPH and PHP studens must receive a final grade of “B –“ or better in each of the following courses:

BIOSTATS 540 – Intrroductory  Biostatistics
EHS 565 – Environmental Health Practices
COM-HLTH 601 – Applications of Social and Behavioral Theory
HPP 620 – Introduction to the US Health Care System
EPI 630 – Principles of Epidemiology
HPP 624 – Research Methods

If a student fails to receive a B- or better in these courses, they will have to repeat the course.

If a student’s overall GPA falls below the 3.0 level, the student will be subject to academic measures pursuant to Section I.4 of the Graduate Student Handbook, including academic probation and/or academic dismissal.

Important Dates to Remember

First Week of Class:
Tuesday- Friday September 5-8, 2017
First Worcester Section Face-to-Face Class: Monday September 11, 2017

Last Day to Drop with no record - Monday September 16, 2017

Holiday, Columbus Day - Monday October 9, 2017
WORCESTER SECTION DOES NOT MEET FACE-TO-FACE
Both sections will work "online" this week


Last Day to Drop with “DR”- Monday October 16, 2017

Fall Semester Thanksgiving Holiday Week Break: Monday-Friday November 20-24, 2017 (No Class)
Both sections will work "online" this week


Last Week of Class
Monday-Tuesday December 11-12, 2017
Last Worcester Section Face-to-Face Class: Monday December 11, 2017

Test 3 (Units 8-10) Due - Monday December 18, 2017

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Course Schedule with Dates of Postings
I am sorry but I do NOT post course materials ahead of schedule.

 

 

Week

Date

Unit - Lecture

Latest Posting Date

1

September 5-8, 2017

Course Introduction

Tuesday September 5, 2017

2

September 11-15, 2017

1 – Summarizing Data

Monday September 11, 2017

3

September 18-22, 2017

2 – Data Visualization

Monday September 18, 2017

4

September 25-29, 2017

3 – Probability: Basics

Monday September 25, 2017

5

October 2-6, 2017

4 – Probabilities in Epidemiology

Monday October 2, 2017

6

Tuesday October 10-13, 2017

5 – Populations and Samples

Tuesday October 10, 2017

7

October 16-20, 2017

6 – Bernoulli and Binomial

Monday October 16, 2017

8

October 23-27, 2017

7 – Normal Distribution

Monday October 23, 2017

9

October 30-November 3, 2017

8 – Statistical Literacty: Estimation and Hypothesis Testing

Monday October 30, 2017

10

November 6-10, 2017

9 – One Sample Inference

Monday November 6, 2017

11

November 13-17, 2017

10 – Two Sample Inference

Monday November 13, 2017

-

November 20-24, 2017

FALL SEMESTER THANKSGIVING BREAK

No Class

12

November 27 - December 1, 2017

11 - Chi Square Tests

Monday November 27, 2017

13

December 4-8, 2017

12- Simple Linear Regression and Correlation

Monday Deember 4, 2017

14

December 11-12, 2017

COURSE CLOSEOUT

Monday Deember 11, 2017

 

 

 

 

 

Test Schedule (duplicated from abov)e:

  Posting Date DUE Date
(Last date for submission for credit)
Test #1
Unit 1 - Summarizing Data
Unit 2 - Data Visualizationa
September 25, 2017
Tuesday October 10, 2017
(October 17, 2017)
Test #2
Unit 3 - Basic Probability
Unit 4 - Probabilities in Epidemiology
Unit 5 - Populations and Samples
Unit 6 - Bernoulli and Binomial Distributions
Unit 7 - Normal Distribution
October 23, 2017
Monday November 6, 2017
(November 13, 2017)
Test #3
Unit 8 - Statistical Literacy
Unit 9 - One Sample Inference
Unit 10 - Two Sample Inference
November 27, 2017
Monday December 18, 2017
(December 20, 2017)


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Policy on Late Submissions (duplicated from above)

On Time
Full Credit for points scored
1-7 Days Late
Points scored - 20 points
8+ Days Late
0 points (no credit)

 

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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
Policy on Academic Dishonesty
.

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University of Massachusetts at Amherst
Copyright 2017 University of Massachusetts, Amherst.
This is the course web site for BIOSTATS 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: September 12, 2017