Biostatistics I
University of Kentucky
STA 580, Spring 2012
Credit: 3.0
Lecture:
Laboratory:
3:30 p.m - 5:20 p.m., Thursday
Room 0014, Charles T. Wethington Building
6:00 p.m - 7:50 p.m., Thursday
Room 602J, College of Nursing
Instructor: Patrick Breheny, Ph.D.
Office: Room 205D, Multidisciplinary Science Building
Phone: 218-2077
e-mail: patrick.breheny@uky.edu
Office hours: Tuesday 1:00 p.m – 4:00 p.m.
Teaching Assistant: Zhiyuan Shen
Office: Room 348, Multidisciplinary Science Building
e-mail: zhiyuan.shen@uky.edu
Office hours: Wednesday 12:00 p.m. – 2:00 p.m.
Course description: STA 580 is an introductory course that covers basic statistics concepts
and methods used in medicine, public health, and the biological sciences. The objectives for
this course are for you to be able to:
• Think statistically – to understand the importance of collecting data and using appropriate statistical methods in order to test hypotheses and conduct research
• Recognize the strengths and limitations of basic statistical techniques
• Conduct analyses using those techniques
• Better comprehend journal articles containing statistical analyses
• Have the necessary background to enroll in Biostatistics II (CPH 630)
Suggested text: No text is required in this course; the notes are self-sufficient. Many students, however, like to purchase a textbook for (a) additional problems/exercises/examples
or (b) another perspective or explanation of a topic. I suggest the following two texts:
• Daniel, W. (2009): Biostatistics: A Foundation for Analysis in the Health Sciences
(Ninth Edition). Wiley.
1
• Motulsky, H. (2010): Intuitive Biostatistics (Second Edition). Oxford University Press.
The book by Daniel is very thorough and provides hundreds of additional examples and
problems. In my opinion, it is the best book for purpose (a) above. The book by Motulsky
attempts to get across the ideas of statistics using verbal explanations and examples rather
than equations. It is quite well-written, does an admirable job of accomplishing its mission,
and is probably the best book for purpose (b) above. There book does not, however, have
problems, solutions, and exercises.
Prerequisite: College algebra.
Course website: The course notes, assignments, data sets, and other relevant materials
will be made available on the course web site:
http://web.as.uky.edu/statistics/users/pbreheny/580-S12/index.html
Grades will also be made available via blackboard, which can be accessed through
https://myuk.uky.edu
Homework: There will be one homework assignment per week, due the following week (i.e.,
homework assigned the day of lecture #1 will be due the day of lecture #2). Homework
will be returned and discussed during the laboratory sections. Solutions will be posted to
blackboard on Friday. Clearly, no homework can be accepted after that (see the section on
grading for ramifications). Electronic submission of homework is acceptable.
You are encouraged to work in groups of two to four, and turn in one copy of the homework
per group. This will make Zhiyuan’s life much easier. If you would like help in finding a
group, please send me an e-mail.
Computing: Homework for this course will involve the use of a computer for data analysis.
You may use any statistical software you would like for this analysis, although the software
packages that will be covered in lab are SAS and R. R is free and open-source. SAS is not; if
you would like to use SAS outside the lab, you can obtain a one-year student license through
UK. If you are interested in doing so, go to download.uky.edu, log in, search for SAS, and
download it. There is also a registration form you need to fill out.
Quizzes: There will be four quizzes in this class. Quizzes will replace the last half-hour of
lecture on the following dates:
Quiz
Quiz
Quiz
Quiz
1
2
3
4
February 2
February 23
March 29
April 19
You will be asked to perform arithmetic calculations on these quizzes, so bring a calculator
with you.
2
Final exam: There will be a comprehensive final exam in this class on Thursday, May
3, from 3:30 p.m-5:30 p.m. (i.e, the same day of the week and time as the regular class
meetings).
Grading: Your grade will be based on a weighted average of homework (26%), quizzes
(37%), and the final exam (37%). Each homework assignment is worth 2% of your grade. If
you fail to turn in a homework assignment, that 2% of weight is added to the quizzes and
final exam (each getting 1%). For example, suppose you only turn in 11 of the 13 homework
assignments; in that case, homework would be worth 22% of your final grade, and quizzes
and the final exam each worth 39%.
In the event that a grade on a homework assignment is lower than your quiz/final average,
that homework will be dropped – i.e., turning in homework cannot hurt your final grade in
this course.
Attendance: Regular attendance in this course is expected. No direct penalty will be applied for missing lectures. However, assignments, quizzes, and the final will be based entirely
on lecture material, so skipping lecture is likely to hurt your grade (and, of course, your
understanding of the material).
Electronic communication: I will occasionally send notices to the class through e-mail
(to the account listed for you in the campus directory), so please check that account regularly.
Cheating: The University of Kentucky takes cheating on examinations very seriously, and
has in place a number of rather severe academic sanctions, a summary of which can be found
at http://www.uky.edu/Ombud/acadoffenses/index.htm
Complaints: Students with suggestions or complaints should see me first, and if we cannot
come to an agreement, I will direct you to the head of the department.
Disabilities: If anyone has a disability requiring special accommodations, please let me
know as soon as possible, so that these arrangements can be made.
I look forward to getting to know you, and I hope that we have a great semester together.
3
Course schedule:
Date
January 12
January 19
January 26
Topics
Introduction; study design
Hypothesis tests and confidence intervals
Observational studies and confounding
Descriptive statistics and graphics
February 2
Correlation and regression
February 9
Probability
February 16
The binomial distribution
One-sample categorical data
February 23 The normal distribution
March 1
The central limit theorem
March 8
Applying the central limit theorem
Approximate inference for one-sample categorical data
March 15
Spring break – no class
March 22
One-sample continuous data
Power and sample size
March 29
Two-sample categorical data (start)
April 5
Two-sample categorical data (end)
Two-sample continuous data (start)
April 12
Two-sample continuous data (end)
April 19
Multiple comparisons and ANOVA
April 26
Survival analysis
May 3
Final exam
Bold denotes the dates of quizzes and tests.
4
ASPH competency attainment for STA 580 – Biostatistics I
Key:
Competency level Number Description
Unaware
0
No information or skill in this area
Aware
1
Able to identify the concept or skill but with limited
ability to perform or apply it independently
Knowledgeable
2
Able to apply and describe the concept or skill
Proficient
3
Able to synthesize, critique, or teach the concept or skill
Biostatistics competencies attained:
Level
Competency
attained
Describe the roles biostatistics serves in the discipline of public health
2
Distinguish among the different measurement scales and the implications for
2
selection of statistical methods to be used based on these distinctions
Apply descriptive techniques commonly used to summarize public health data
2
Describe basic concepts of probability, random variation, and commonly
2
used statistical probability distributions
Apply common statistical methods for inference
2
Describe preferred methodological alternatives to commonly used
2
statistical methods when assumptions are not met
Apply descriptive and inferential methodologies according to the type
2
of study design for answering a particular question
Interpret results of statistical analyses found in public health studies
2
Develop written and oral presentations based on statistical analyses
1
for both public health professionals and educated lay audiences
Apply basic informatics techniques with vital statistics and public
1
health records in the description of public health characteristics
and in public health research and evaluation
5