SAN DIEGO STATE UNIVERSITY Graduate School of Public Health

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SAN DIEGO STATE UNIVERSITY
Graduate School of Public Health
Division of Epidemiology and Biostatistics
PH 602 Biostatistics
Fall 2010
Section
1
Day
Tuesday
Instructor: John Alcaraz, Ph.D.
Office phone: (619) 594-1342
E-mail:jalcaraz@mail.sdsu.edu
Time
4:00p – 6:40p
3 units
Location
HH 222
Schedule No.
22290
Office location: Hardy Tower 231
Office hours: Mon Wed 12:30p – 1:50p
Tuesday
2:00p – 3:50p
Blackboard:
During the semester, course-related materials such as announcements, homework solutions, and
sample exams will be posted on Blackboard. Please check regularly for new materials.
Required Texts:
– Rosner: Fundamentals of Biostatistics, 6th Edition.
– Alcaraz: “PH 602 Lecture Notes” (Lecture notes should be brought to every class meeting.)
Calculator:
Students will need a scientific calculator which, in addition to performing the basic arithmetic
operations, should have at least the following functions: x 2 , x , y x , e x , and ln (natural log).
Grading System:
Exam I:
Exam II:
Final Exam:
25%
25%
50%
93 – 100 = A
90 – 93 = A–
87 – 90 = B+
83 – 87 = B
80 – 83 = B–
77 – 80 = C+
73 – 77 = C
70 – 73 = C–
67 – 70 = D+
63 – 67 = D
60 – 63 = D–
0 – 60 = F
Exams:
All exams are in-class, open-book and open-notes, and calculators are required. The dates below
are subject to change:
Exam
Date
Chapters in Lecture Notes
I
September 28
Ch 3–6
II
November 2
Ch 7–9, part of 10
Final part 1
November 30
Ch 3–9
Final part 2
December 7
Ch 10–12
Exercises:
Exercises will include problems assigned from the text or from other sources. Although the
exercises will not be graded, you are expected to complete them. Solutions will be posted on
Blackboard. If time permits, some exercises may be discussed in class.
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Prerequisite:
Passing the competency exam in basic statistical methods or successful completion of STAT 119
or STAT 250 or successful completion of an approved basic statistics course within the past three
years. Students must complete the prerequisite prior to enrollment.
Background:
Students are expected to know descriptive statistics (Ch 2, Rosner); this material will not be
covered in the course. Students should be familiar with basic concepts of probability (3.1 – 3.6,
Rosner), the binomial distribution (4.8 – 4.9), the normal distribution (5.3 – 5.4), basic concepts
of estimation (6.1 – 6.3), and basic concepts of hypothesis testing (7.1 – 7.2). These topics will be
reviewed in the lectures; however, extensive discussions of this material will not be pursued.
Learning Objectives:
In this course, students will learn basic biostatistical methods used in biomedical and public
health research. Students will be able to recognize and apply the appropriate biostatistical
procedures to the analysis of health-related studies. Students will learn
1. To recognize the appropriate use of the binomial, normal, Student’s t, chi-square and F
distributions in estimation and hypothesis testing.
2. To describe the relationship between populations and samples, and the crucial role that
random sampling plays in statistics.
3. To estimate such parameters as means, variances, and proportions, and to test hypotheses
about these parameters (confidence intervals, one-sample test for proportion, one-sample ttest, two-sample t-test, paired t-test).
4. To apply nonparametric tests (Wilcoxon signed-rank test, Wilcoxon rank-sum test) when the
underlying distributional assumptions are not met.
5. To assess the association—through relative risk or odds ratio estimation and through
hypothesis testing (contingency tables)—between two variables when both variables
represent groupings into categories or classes.
6. To understand the appropriate use of simple linear regression and correlation, and to estimate
parameters and test hypotheses about linear relationships.
7. To complete a one-way analysis of variance model for comparing three or more means, and
to describe procedures for performing multiple pairwise comparisons among these means.
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Academic Ethics:
SDSU has a strict code of ethical conduct which students are expected to follow.
Seehttp://csrr.sdsu.edu/conduct1.htmlfor details. In particular, cheating on the exams will not be
tolerated. You may not work together on the exams, may not copy answers from other students,
and may not allow other students to copy your answers. Anyone caught cheating will face
disciplinary action.
Attendance/Punctuality:
While attendance is not required except for exam dates, students are strongly encouraged to
attend every class meeting and to be punctual. On exam dates, the exam will start at 4:00pm sharp
and will end at 6:40pm sharp. Those who arrive late on exam dates will not be allowed to work
past the end time to complete their exams.
If you miss an exam because of severe circumstances (such as illness, injury, death in the family),
please contact me no later than one week after the exam to arrange a makeup test.
Students for whom an exam falls on a date of religious observance should contact me by the end
of the second week of classes to discuss alternative arrangements.
Students with Disabilities:
Students with disabilities should discuss with me privately any specific accommodations for
which they have received authorization. Authorization may be obtained by contacting Student
Disability Services at 619-594-6473 (Calpulli Center, Suite 3101). Please obtain authorization
before making an appointment to see me. More information can be found at
http://www.sa.sdsu.edu/sds/.
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Course Outline for PH 602
Topic
Chapters in Rosner
Review of basic concepts of probability
Applications of Bayes’ rule
3.1 – 3.6
3.7
Probability distributions
Discrete
Basic ideas
Review of the binomial distribution
Continuous
Basic ideas
Review of the normal distribution
Normal approximation to binomial
Week *
1
1
5.1, 5.2
5.3, 5.4, 5.5
5.7
1
1
1, 2
2
2
2
2
2, 3
Review of populations and samples
Review of random sampling
Sampling distribution
Estimation: Point and interval
6.1, 6.2
6.3
6.5
6.5, 6.7, 6.8
3
3
3
3
Hypothesis testing
Review of basic concepts
One-sample problem
Two-sample problem
Nonparametric statistics
Hypothesis tests for categorical data
Simple linear regression
Correlation
Analysis of variance
7.1, 7.2
7.3 – 7.7, 7.9, 7.10
8.1 – 8.7, 8.10
9.1, 9.3, 9.4
10.1 – 10.6, 13.3, 13.5
11.1 – 11.5
11.7, 11.8
12.1 – 12.4
4.1 – 4.7
4.8, 4.9
4
4
4, 6
6
6, 7
7, 8, 9
9
11
11
* Week of the semester (see next page). Timeline is approximate and subject to change.
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Course Outline for PH 602
Week *
1
Date
Aug 31
Topics
Basic probability concepts, conditional probability, relative risk,
screening tests, discrete random variables
2
Sept 7
Discrete random variables (cont.), binomial distribution, hypothesis
testing preview (p-value), continuous random variables, properties
of all random variables, normal distribution
3
Sept 14
Normal distribution (cont.), populations and random samples,
estimating the mean of a distribution, estimating the variance of a
distribution, estimating a binomial proportion
4
Sept 21
Review of hypothesis testing concepts, one-sample z test, onesample t test, one-sample test for binomial proportion
5
Sept 28
Exam I
6
Oct 5
One-sample test for binomial proportion (cont.), paired- versus
independent-sample designs, paired t test, two-sample t test, intro to
nonparametric tests
7
Oct 12
Wilcoxon signed-rank test, Wilcoxon rank-sum test, chi-square test
for 2x2 contingency table
8
Oct 19
Chi-square test for 2x2 contingency table (cont.), Mantel-Haenszel
test for 2x2 contingency tables, chi-square test for RxC contingency
table, McNemar’s test for paired samples
9
Oct 26
McNemar’s test for paired samples (cont.), simple linear regression
10
Nov 2
Exam II
11
Nov 9
Correlation, overall F test for one-way ANOVA, post-hoc testing
(multiple comparisons)
12
Nov 16
Course review (Open Q&A)
13
Nov 23
No class
14
Nov 30
Final Exam part 1
15
Dec 7
Final Exam part 2
* Timeline is approximate and subject to change.
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Association of Schools of Public Health
Core Competencies in Biostatistics
BIOSTATISTICS
Biostatistics is the development and application of statistical reasoning and
methods in addressing, analyzing and solving problems in public health; health care;
and biomedical, clinical and population-based research.
Competencies: Upon graduation a student with an MPH should be able to…
1.
Describe the roles biostatistics serves in the discipline of public health.
2.
Describe basic concepts of probability, random variation and commonly used
statistical probability distributions.
3.
Describe preferred methodological alternatives to commonly used statistical
methods when assumptions are not met.
4.
Distinguish among the different measurement scales and the implications for
selection of statistical methods to be used based on these distinctions.
5.
Apply descriptive techniques commonly used to summarize public health data.
6.
Apply common statistical methods for inference.
7.
Apply descriptive and inferential methodologies according to the type of study
design for answering a particular research question.
8.
Apply basic informatics techniques with vital statistics and public health records in
the description of public health characteristics and in public health research and
evaluation.
9.
10.
Interpret results of statistical analyses found in public health studies.
Develop written and oral presentations based on statistical analyses for both
public health professionals and educated lay audiences.
Source: ASPH Education Committee, “Master’s Degree in Public Health Core Competency
Development Project: Version 2.3,” Association of Schools of Public Health, October 2004August 2006, p. 12<http://www.asph.org/userfiles/version2.3.pdf>.
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