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APTSA-GE2995/GPH-GU-2995
Biostatistics I, Fall 2014
Instructor:
Email:
Phone:
Office/Box:
Office Hours:
Ryan Richard Ruff
[email protected]
212.998-9663
250 Park Avenue South, 6th Floor
TBD and by appointment
TA: TBD
Class Meeting Time/Room: Tuesdays, 4:55-6:35, 401 Silver
Lab Meeting Time/Room: Tuesdays, 6:45-8:00, TISC LC19
COURSE OVERVIEW
This course is cross-listed under APTSA-GE-2995 and GPH-GU-2995. The course sequence is intended
for graduate students in public health and epidemiology. It provides both the foundations necessary for
Biostatistics II and serves as a stand-alone introductory statistics course. It will concentrate on the
interpretation and comprehension of graphical and statistical techniques that are important components of
scientific literature. Mathematical ability at the level of high school algebra is required. Data analysis using
SPSS is also an important component of the class. There will be SPSS lab sessions covering the topics of
data management and statistical analysis.
OBJECTIVES
At the conclusion of this course the student will be able to:
 Apply critical evaluation skills to the reading of scientific research presentations as they relate to:
sample statistics, simple hypothesis tests, mean comparison and ANOVA.
 Understand the principles of probability theory as a basis for making statistical decisions.
 Perform statistical analyses covered in class using the SPSS statistical program.
 Combine their knowledge of statistical analysis and use of SPSS to perform an analysis of real
data to answer scientific hypotheses.
 Undertake further study of statistics based on the Biostatistics II course.
ASPH CORE COMPETENCIES
Students 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. Interpret results of statistical analyses found in public health studies
10. Develop written and oral presentations based on statistical analyses for both public health
professionals and educated lay audiences
ASPH CROSS-CUTTING COMPETENCIES
1. Use information technology to access, evaluate, and interpret public health data (F8)
2. Articulate an achievable mission, set of core values, and vision (H3)
3. Engage in dialogue and learning from others to advance public health goals (H4)
4. Apply biological principles to development and implementation of disease prevention, control, or
management programs (I8)
5. Apply evidence-based principles and the scientific knowledge base to critical evaluation and
decision-making in public health (J3)
6. Apply the core functions of assessment, policy development, and assurance in the analysis of
public health programs and their solutions (J4)
TEXTBOOKS
Readings will include a course textbook, additional resources, and reference materials.
a. Course textbook: Gertsman, Basic Biostatistics: Statistics for Public Health Practice (2014). Jones
& Bartlett Learning, 2nd edition
b. Additional online readings showing the use of concepts in applied research will be posted
c. We also recommend using http://seeingstatistics.com which has many demonstrations of statistical
concepts using Java.
OTHER NEEDS
Software:
The statistical software package SPSS will be used intensively in this course. It is highly
recommended that you obtain a copy at NYU computer store. You can also access SPSS
in most NYU computer labs as well as via the virtual lab at
https://vcl.nyu.edu/vpn/index.html
Calculator:
A basic scientific calculator is needed.
iClicker:
iClicker will be used as a tool for interactive teaching. A satisfactory iClicker record
(90% participation or higher) is required for you to receive a full participation grade. It is
your responsibility to bring the iClicker to class.
COURSE REQUIREMENTS
Homework
Ten homework sets will be assigned during the course. A typical homework involves understanding of the
statistical concepts, using SPSS to analyze data and interpreting the results, with only minimal manual
calculation. Homework assignments are automatically administrated through NYU Classes. Each
assignment will be available online for approximately a week. You will need to complete the assignment
online and will receive instant feedback upon completion. The homework will become unavailable after its
due time. This means it is not possible to turn in late homework.
Projects
Two projects will be assigned during the course. Both projects consist of the analysis of a public health or a
biological data set. The projects are to be typed and should be professional in appearance. Hand written
projects will not be graded. The project is to be worked on and written up independently. Plagiarism will
result a grade of 0. By plagiarism we mean either using all or any part of other students’ work as your own
or allowing others to use all or any part of your own work.
Exams
There will be both a midterm and final exam. Each will contain both general statistical knowledge
questions and a series of statistical analyses with questions relating to the theory used, assumptions made,
and interpretation of the statistical data presented. They do NOT emphasize calculations and formulas.
Material from both the lectures and from the text may appear on the exam and all exams are cumulative.
GRADE DISTRIBUTION
Weekly Homework
Projects (2)
Midterm
Cumulative Final
Participation
SCHEDULE
Week 1 (09/02)
Week 2 (09/09)
Week 3 (09/16)
Week 4 (09/23)
Week 5 (09/30)
Week 6 (10/07)
Week 7 (10/14)
Week 8 (10/21)
Week 9 (10/28)
Week 10 (11/04)
Week 11 (11/11)
Week 12 (11/18)
Week 13 (11/25)
Week 14 (12/02)
Week 15 (12/09)
Week 16 (12/16)
10%
30% (15% each)
20%
30%
10% (assessed through iClicker)
Overview
Data Visualization: Graphs and Tables
Central Tendency
Variability
Statistical Inference: Samples to Population
Confidence Intervals of sample estimates
Fall Recess
Midterm (Project one due)
Probability and the Normal Distribution
Hypothesis Testing: One Sample
Hypothesis Testing: Two Samples
One Way Analysis of Variance
Nonparametric Statistics
Epidemiological Study Design/Analysis
Review (Project two due 12/13)
Final Exam 75 minutes
*The course schedule is tentative and subject to revisions during the course.
Reading Assignments (TBA)
Week 1 (09/02)
Overview
Gertsman Chapter 1, 2
Week 2 (09/09)
Gertsman Chapter 3
Data Visualization
Week 3 (09/16)
Central Tendency
Gertsman Chapter 4.1, 4.2, 4.3, 4.4
Week 4 (09/23)
Variability
Gertsman Chapter 4.5, 4.6, 4.7, 4.8
Week 5 (09/20)
Gertsman Chapter 5, 8
Statistical Inference: Samples to Population
Week 6 (10/07)
Gertsman chapter 10
Confidence Intervals of sample estimates
Week 9 (10/28)
Gertsman chapter 6, 7
Probability and the Normal Distribution
Week 10 (11/04)
Gertsman chapter 9, 11
Hypothesis Testing: One Sample
Week 11 (11/11)
Gertsman Chapter 12
Hypothesis Testing: Two Samples
Week 13 (11/18)
Gertsman Chapter 13
One Way Analysis of Variance
Week 14 (11/25)
Nonparametric Statistics
Readings to be announced
Week 15 (12/02)
No readings
Epidemiological Study Design/Analysis
Students With Disabilities
Any student attending NYU who needs an accommodation due to a chronic, psychological, visual, mobility
and/or learning disability, or is Deaf or Hard of Hearing should register with the Moses Center for Students
with Disabilities at 212 998-4980, 726 Broadway, 2nd Floor, http://www.nyu.edu/csd. Information about
the Moses Center for Students with Disabilities must appear on the syllabus. If a student presents
documentation from the Moses Center suggesting that unique considerations be applied for that student’s
optimal learning, please feel free to consult with the Moses Center or Julie Avina, Associate Dean of
Student and Alumni Affairs.