STA1403
SPRING 2015 SYLLABUS
MICHAEL ANDERSON
BB 4.04.28
458-6344
Abstract. STA1403 Probability and Statistics for the Biosciences
[TCCN: MATH 2442.] (3-0) 3 hours credit. Prerequisite: MAT 1194
or an equivalent. Probability and statistics from a dynamical perspective,
using discrete-time dynamical systems and differential equations to model
fundamental stochastic processes such as Markov chains and the Poisson
processes important in biomedical applications. Specific topics to be covered
include probability theory, conditional probability, Poisson processes, random
variables, descriptive statistics, covariance and correlations, the binomial
distribution, parameter estimation, hypothesis testing and regression. Meets
Mondays, Wednesdays, and Fridays, 9:00-9:50am (Section 001), 11:00-11:50am
(Section 002), or 2:00-2:50am (Section 004), in rooms BB 2.01.14, BB 2.01.18,
and BB 2.01.18, respectively.
“Yesterday I dared to struggle. Today I dare to win.” –Bernadette
Devlin
1. Course Resources
1.1. Textbook.
• Elston and Johnson,
Basic Biostatistics for Genetecists and
Epidemiologists, (E&J, required)
The Elston and Johnson text is available as an e-book through the UTSA library
and on the course blackboard site.
1.2. Course Materials. All course materials and schedules are available on
UTSA’s Blackboard site at http://learn.utsa.edu/.
1.3. Office Hours. (Mondays and Fridays 12:00noon – 1:45pm, in in the Stats
Lab, BB 3.02.16, and by appointment) Office hours are held to help you with
the material and me with tracking how well I’m teaching it. I’ll gladly give you
homework hints and pointers for other courses. If you have a question and can’t
make office hours, either set up an appointment with me, or send the question by
Blackboard e-mail.
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MICHAEL ANDERSON
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BB 4.04.28
458-6344
topic
EDA and Probability Models
populations and samples
experiments
–exercise 1: sampling and experiments
MARTIN LUTHER KING, JR., HOLIDAY
descriptive statistics
–exercise 2: descriptive statistics
probability
random variables
–exercise 3: probability
distributions
the Gaussian distribution
–exercise 4: random variables
EXAM 1
Basic Inference
interval estimates
multiple samples
correlation
–exercise 5: estimation
single-sample tests
power and sample size, meta-analysis
–exercise 6: hypothesis testing
two-sample and paired tests
likelihood and Bayesian methods
–exercise 7: two-sample tests
SPRING BREAK all week!
Modeling
tests of fit and homogeneity
–exercise 8: chi-square tests
EXAM 2
one-way ANOVA
factorial ANOVA, ANCOVA
model-checking
–exercise 9: ANOVA
simple regression
intervals and diagnostics
–exercise 10: OLS
multiple regression
dummies and interactions
–exercise 11: multiple regression
the logistic regression model
ROC curves
–exercise 12: logistic regression
survival analysis
EXAM 3
COMPREHENSIVE FINAL section 004
COMPREHENSIVE FINAL section 001
COMPREHENSIVE FINAL section 002
reading
E&J, Chs 1, 2
E&J, Ch 3
E&J, Ch 4
E&J, Ch 5
E&J, Ch 6
E&J, Ch 7
E&J, Ch 8
E&J,Ch 8
E&J, Ch 9
E&J, Ch 11
E&J, Ch 12
handout
12:30–3:00pm
7:00–9:30am
9:45am–12:15pm
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1.4. Lectures. Lectures will cover difficult topics from each of the sections
assigned, but they are not intended to comprehensively cover each topic. There
simply is not enough time; instead you are expected to study the simpler material
as part of your course preparation. Each topic block in the course has a list of
study problems (the topic contents pages on Blackboard) which you should read
prior to attending lecture; these will be the basis for graded classroom exercises.
You should also learn the technical terms in the readings; students will also be
called at random to explain terminology.
2. Course Work
Eighty percent of success is showing up. –Woody Allen
2.1. Grading. Grades are assigned by point totals.
assignment type
max points
class exercises (12)
300
online exercises (6)
150
case studies (9)
450
examinations (3)
300
problem sets (12)
300
extra credit
100
total available
1600
You must accumulate at least 700 points to pass this course; the minimum
passing grade is a D. Minimum point requirements for grades are D - 700, C 800, B - 900, A - 1000. Two letter grades will be published on the Blackboard
web site after each exam; one (ASAPmidterm) is a “pro-rated” grade based on
the proportion of material covered in the syllabus, the other (ASAPfinal) is your
raw grade. If you have a failing grade after the first examination, this is a clear
indication that you are not able to apply sufficient resources to successfully complete
the course, and you should drop.
Interpretation of grades:
A: You have a clear understanding of this course material. You are ready to
take further courses in theoretical or applied statistics.
B: You have a reasonable grasp of this material. You are ready for further
courses in applied statistics, but you will need to brush up to be successful.
C: You are familiar with basic terms and ideas in statistics, and are ready
to see these again in some of your biology courses. However, you should
probably avoid statistics in the future.
D: You and statistics are incompatible. Focus on qualitative, rather than
quantitative, work.
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MICHAEL ANDERSON
BB 4.04.28
458-6344
A man wandering in downtown Manhattan stops a fellow carrying a
clarinet case and asks him, “Excuse me, how can I get to Carnegie
Hall?”
“Practice!” replies the musician.
2.2. Online Exercises. These exercises are available on the course Blackboard
site. Each exercise is a set of 25 questions chosen at random from a question
bank; some are multiple-choice, others involve calculations. You may attempt each
exercise an unlimited number of times, you will receive the highest score achieved
on each exercise. Exercises must be completed by the last day of class.
2.3. Classroom Exercises (“Not at home” work). During some class meetings
you will work in small groups to solve a set of problems suggested by the lectures.
You should discuss and attempt to resolve any technical questions about problemsolving within your group before asking me for help. Each group will mark their
solutions on the answer form provided.
You must learn from the mistakes of others. You can’t possibly live
long enough to make them all yourself. - Sam Levenson
2.4. Problem Sets. These are sets of related problems that illustrate key
statistical techniques, which require only a simple calculator to solve. Your
write-up should form a coherent narrative, with explanatory comments for any
derivations or calculations. DO NOT SHOW EVERY MINOR ALGEBRAIC OR
ARITHMETIC STEP in derivations or calculations, only those steps necessary to
understand how the result was obtained. Edit your write-ups just as you would
an essay or term paper; there should be no misspellings, sentence fragments, or
meandering blather. Your submissions should be handwritten, then scanned as a
PDF or image file, and submitted via Blackboard.
2.5. Case Studies. Case studies are analyses from the textbook and readings,
intended to apply the basic computational and inference skills you are learning in
this course and its prerequisite. All case studies will be available the first week of
class, and are to be done individually, unless otherwise noted. Submit your writeup for each case study online via Blackboard. No submissions will be accepted late
unless you have made confirmed prior arrangements with me.
Case studies should be concise word-processed documents in either Word
document (*.DOC, *.DOCX) or Adobe portable document (*.PDF) format.
Include the problem statement, as well as the analysis, including any supporting
statistics and graphics. Graphics generated by MATLAB or other software should
be included in the body of your narrative as illustrations of your data, analysis,
or conclusion. I recommend that analyses done using MATLAB be processed with
the Publish facility to generate your write-up. Be sure to include your name and
UTID number (the xyz666 one).
Case studies are graded according to published rubrics. Points are awarded for
various analytical steps (summary statistics, data graphics, fitted models, etc.) as
well as narrative clarity, completeness, format, and organization.
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Common (point-losing) mistakes are unlabeled graphs, incorrect terminology,
misplaced decimal points, etc. Don’t lose points by being sloppy or ignoring
directions!
2.6. Plagiarism. The University has a strict policy on plagiarizing coursework.
Because I am averse to investigations into culpability and the attendant paperwork,
I have a simple policy for homeworks that are substantially identical. The first copy
is graded as though it were original work to get a point total. That point total is
then divided equally among all the copies that I receive. For example, if a problem
set is submitted in 4 copies, and it gets a 48, then the 4 individuals involved each
get 12 points for their effort.
2.7. Examinations. The examinations have problems similar to those in the
classroom and online exercises. You will need pencils, and eraser, a calculator,
and a large-format bluebook. There will also be a section of multiple-choice
questions; Scantron forms will be provided. You may bring a single 3 × 5” formula
card to the exam. Exam results will be posted to Blackboard two days after the
exam date. If you are unable to sit for an exam on the scheduled date, you have
should take the exam during the following class meeting or during the course final
examination period.
2.8. Extra Credit. There will be several opportunities throughout the semester
to earn extra credit. You can earn up to 10 points for attending a statistics or
computational biology colloquium and writing a brief report on it. Other extracredit opportunities will be announced in class. Extra credit write-ups are due no
later than the Friday of the week following the assignment or event, and should be
submitted via Blackboard in the Extra Credit discussions.
3. Class Policies
3.1. Attendance. Class attendance is vital, since most of the material will be
presented by students in discussion or solved problems. A sign-in roster will be
passed around at the beginning of each class; be sure to initial it. This roster tells
me (a) if you’ve been attending class, (b) when you stopped attending if you drop
out, and (c) whether you’re present in the event of an emergency. If I am more than
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MICHAEL ANDERSON
BB 4.04.28
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5 minutes late to the lecture, you should assume I have been unavoidably detained,
and the lecture is cancelled.
3.2. Behavior. Your class behavior should be courteous, relaxed, and
participative. You are expected to assist in maintaining an environment that is
conducive to learning. To assure everyone has an opportunity to gain from time in
class, do not engage in any form of distraction. If you behave inappropriately, you
will be, at a minimum, asked to leave class. You are encouraged to ask any and all
questions about the material, including fishing for hints about homework problems.
If a proof or calculation on the blackboard is unclear or has an error, sing out! If
you have question about outside material that is relevant, feel free to ask that as
well.
3.3. Enrollment. Enrollment in class is your responsibility. If you’re not enrolled,
it is a violation of Texas law for you to attend classes. There are no automatic drops
for course non-attendance. If you do not drop, and fail to complete sufficient course
work, you will receive a failing grade.
3.4. Materials and Resources.
3.4.1. Calculator. You will need a scientific calculator for class exercises, quizzes,
and the midterm. It need not be very sophisticated, but it should be able to
calculate logs, exponentials, square roots, and factorials.
3.4.2. Computer Storage Media. Problem sets, solutions, and course supplements
are provided as PDFs on the course Blackboard site. Some homework problems
require simple MATLAB programs to analyze data. For all of these, you will need
some sort of removable medium, e.g. a flash drive, to save your course work.
3.4.3. Tutoring. Academic support services are available to you through the Toms
Rivera Center (TRC)for building study skills and tutoring in course content. These
services are available at no additional cost to you. The TRC has several locations
at the Main Campus and is also located at the Downtown Campus. For more
information, visit the web site at www.utsa.edu/trcss or call (210) 458-4694 on the
Main Campus and (210) 458-2838 on the Downtown Campus.
3.5. Right to Privacy. Except under specific exceptions provided in the Family
Education Rights and Privacy Act of 1974, I will not give information concerning
your grades, academic progress, attendance, address, phone, or email to anyone
outside the UTSA system unless you give your prior written permission. I will not
give or discuss grade information over the phone or via email.
3.6. Special Needs. If you feel that you are eligible for or may be helped by
accommodations in the class due to a disability or special need, contact the
Office of Disability Services (ODS). Students with disabilities must be registered
with the ODS located in MS 2.03.18 (458-4157 - voice; 458-4981 - TRY) or
UTSA Downtown in FS 1.526 (458-2816), in order to receive support services.
To see if you are eligible for these services and privileges, visit the website
http://www.utsa.edu/disability/studeligibility.htm.
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3.7. Academic Conduct. The UTSA Honor Pledge states
On my honor, as a student of The University of Texas at San
Antonio, I will uphold the highest standards of academic integrity
and personal accountability for the advancement of the dignity and
the reputation of our university and myself.
The UTSA Information Bulletin, 2008-2009 states
Sec. 203. Scholastic Dishonesty
A. The Office of Student Judicial Affairs or faculty may initiate
disciplinary proceedings against any student accused of scholastic
dishonesty.
B. “Scholastic dishonesty” includes, but is not limited to,
cheating, plagiarism, collusion, falsifying academic records, and any
act designed to give unfair advantage to the student (such as, but
not limited to, submission of essentially the same written assignment
for two courses without the prior permission of the instructor,
providing false or misleading information in an effort to receive a
postponement or an extension on a test, quiz, or other assignment),
or the attempt to commit such an act.
(http://www.utsa.edu/infoguide/appendices/b.html)
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MICHAEL ANDERSON
BB 4.04.28
458-6344
4. Frequently Asked Questions
4.1. Can I turn my homework in late? No. It’s posted at the beginning of the
semester; how much lead time do you need?
4.2. Can I turn my homework in early? You betcha! See the final question
for why you might want to do that.
4.3. I didn’t attend class last time. Did I miss anything important?
Yes. Many instructors try to encourage class participation by telling students to
be uninhibited about asking questions. “There are no stupid questions,” they say.
What a crock. “Did I miss anything important?” is the original stupid question.
4.4. Is class attendance mandatory? No. This is not high school. If you miss
a class, I assume you had another commitment with a higher priority, and that you
will do the reading and study necessary to catch up. If you chronically miss class,
I assume you’ve lost interest in the course, and are willing to settle for a less than
excellent–perhaps even less than passing–grade.
4.5. Can I do any extra-credit assignments to improve my grade? Yes, all
semester. Get busy.
4.6. I wasn’t in class for the last exercise. How can I make it up? If you
miss a classroom exercise, we’ll probably notice your absence (by lack of a score)
and we will provide you access to an online version of the exercise, with one week
to complete it. Get it done on time, or not at all.
4.7. There are 1500 points worth of assignments, but I only need 1000
points to get an A. What happens if I hit 1000 before the end of the
semester? Congratulations, you’re done. Go work on your other courses.