Introduction to Biostatistics: Basic for Public Health
Part 1: Course Information
Instructor Information
Instructor : Professor dr. Siswanto Agus Wilopo, S.U,
M.Sc., Sc.D.
Office : Gedung IKM Room 001, Jl. Farmaco 1, Bulaksumur,
Yogyakarta
Office Hours : 08.0-10.00 & Monday
and Wednesday
Office
Telephone : 62-274-548-156 or
5656076
E-mail : sawilopo@ugm.ac.id
Teaching Assistant
Coordinator : dr. Amirah Ellyza Wahdi, MSPH
Office : Gedung IKM Room 008, Jl. Farmaco 1,
Bulaksumur, Yogyakarta
Office Hours : 08.0-10.00 & Tuesday
and Thursday
Office
Telephone : 62-274-548-156 or
5656076
E-mail : amirahellyzawahdi@ugm.ac.id
Course Description
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. This course will cover descriptive statistics,
probability theory, and a wide variety of inferential statistical techniques
that can be used to make practical conclusions about empirical data derived
from public health works. We will use two approaches to the mastery of the
course materials: a) students will look in some detail at how statistical
procedures are employed and b) students will conduct several basic procedures
by exercising with real data to fully understand the logic and application of
statistics. In addition, the student
will learn how to use a computer package, STATA, to quickly perform statistical
analyses in more complex situations and how to interpret the results of the
data analyses. Using this approach will enable students to be educated users
and producers of statistical knowledge in the real world, which is the
application of statistics in public health and
medical settings. This course is mandatory for Graduate and MPH students.
Prerequisite
Students should be familiar with basic mathematical
calculation, probability, and the use of a computer.
Textbook & Course Materials
Required Text
- Pagano, M. Gauvreau, K. and Mattie, H (2022). Principles
of Biostatistics. Third Edition CRC Press:
6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742
- Rosner
B (2016). Fundamentals of Biostatistics, 8th ed. California: Cengage
Learning pp:1-888.
- Copies of the lecture notes (pdf) may be
obtained at the Web Course (Elok or Gamel).
Recommended Texts & Other Readings
- Etzioni,
Ruth; Mandel, Micha; Gulati, Roman (2021). Statistics for Health Data
Science An Organic Approach. Gewerbestrasse 11, 6330 Cham, Switzerland: Springer
Nature Switzerland AG.
Course Requirements
The course requirements are intended to help students understand and apply
for the course material. The weekly discussion
with the teaching assistant will test students’ understanding of the readings. The written
assignments focus on the application of the course material to specific health development
projects. Students should upload each
assignment to the appropriate Elok discussion thread by the deadlines posted. The
student should have the following:
- Internet connection (DSL, LAN, or cable
connection desirable).
- Access to Website/Other
- Software Stata which can be accessed at Medica
Library.
Course Structure
This course
will be delivered in lectures and discussions during laboratory sessions using an
online and hybrid approach (when it is possible). The lecture will be given twice
weekly or depending on the department’s schedule. In each topic, the lecturer
will present statistical theory or concepts and will discuss them within the
class. The instructor will assign the exercises (homework) at the end of each laboratory
session as stated in the lecture module. Exercises reinforce quantitative
skills and specific content areas. During the course, students will experience
and apply their knowledge through the development of data analysis given in the
exercise or laboratory module.
Enrolment
This
course is open to a limited number of individuals outside of the MPH's
programs. Preference is given to UGM-affiliated students,
including doctorate students. We regret that auditing is not permitted. To
apply for this course please fill out and apply available at the study program. The cost and
submission information is in
the application form.
Lecture Topics
The lecture will cover
statistical theories and their
application to
health research. It will be given at least twice a week (Tuesday and Thursday:
10.00-12.00). Each session is about 100 minutes.
There will be 14 sessions of lectures during this class and 12 Laboratory modules.
Laboratory Exercise
Students
will be allowed to
explore further details of the lecture materials in the form of discussion and
exercise in the class. The teaching assistant and computer programmer are
assigned to lead this class discussion and exercise. Their tasks provide
student’s better understanding
of the
lecture materials and problem sets for the previous homework.
Problem Sets for Homework
Problem
sets require the use of STATA (or a comparable statistics package, such as R).
You will need to submit a STATA code (or code from an equivalent package.
If you are using STATA, the code is automatically generated for you as a log file. You need to cut
and paste the relevant code from this automatically generated code into your
homework (which will take some understanding of the code itself).
Online Resources
All lecture
and laboratory materials are distributed in the Web class. These resources are available in Elok or Gamel.
Part 2: Student Learning Outcomes
Learning Objectives
This course will explain how to:
- Formulate
the proper statistical technique to be used in analyzing data sets (e.g.,
exploratory data analyses or EDA) for continuous or count data, parametric or non-parametric
methods, and independent or paired samples).
- Apply
statistical knowledge to designing research studies. This includes computing
the sample sizes necessary to show the statistical significance and selecting
the proper study design.
- nalyze
public health data with proper statistical techniques using a computer
statistical software package (Stata).
- Interpret
computer outputs for the more commonly used statistical tests in the public
health field.
- Appraise
public health and scientific journal articles that frequently rely heavily on
statistical procedures, such as linear regression, logistic regression, and
survival analysis.
Learning Outcomes
By the end of
this course, students should be able to:
- Describe
the roles biostatistics serves in the discipline of public health.
- Describe
the basic concepts of probability, random variation, and commonly used
statistical probability distributions.
- Describe
preferred methodological alternatives to commonly used statistical methods when
assumptions are not met.
- Distinguish
among the different measurement scales and the implications for the selection
of statistical methods to be used based on these distinctions.
- Apply
descriptive techniques commonly used to summarize public health data.
- Apply
common statistical methods for inference.
- Apply
descriptive and inferential methodologies according to the type of study design
for answering a particular research question.
- Apply
basic informatics techniques with vital statistics and public health records in
the description of public health characteristics and public health research and
evaluation.
- 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.
Part 4: Grading Policy
Graded Course Activities
Final grades assigned for this course will be based on the percentage
of total points earned and are assigned as follows:
Laboratory Assignment
|
:
|
30%
|
Midterm exam
|
:
|
20%
|
Final Exam
|
:
|
50%
|
Letter Grade
|
|
|
Letter
Grade
|
|
A
|
4.00
|
|
C+
|
2.25
|
A-
|
3.75
|
|
C
|
2.00
|
A/B
|
3.50
|
|
C-
|
1.75
|
B+
|
3.25
|
|
C/D
|
1.50
|
B
|
3.00
|
|
D+
|
1.25
|
B-
|
2.75
|
|
D
|
1.00
|
B/C
|
2.50
|
|
E
|
0.00
|
Part 5: Course Policies
Attend Class
Students are expected to attend
all class sessions and laboratory exercises as listed on the course calendar. If
a student attends less than 75% of class or laboratory exercises is not given a
final grade.
Participate
The Laboratory
session must be attended by all students. The students will be divided into groups
and randomly selected by the Teaching assistant coordinator. The teaching
assistant will record your class activities as part of your grade.
Build Rapport
If you find
that you have any trouble keeping up with assignments or other aspects of the
course, make sure you let your instructor know as early as possible. As you
will find, building rapport and effective relationships are key to becoming an
effective professional. Make sure that you are proactive in informing your
instructor when difficulties arise during the semester so that they can help
you find a solution.
Completed Assignments
All
assignments for this course will be submitted electronically through Elok
unless otherwise instructed. Assignments must be submitted by the given
deadline or special permission must be requested from the instructor before the
due date. Extensions will not be given beyond the next assignment except under
extreme circumstances. All discussion assignments must be completed by the assignment's
due date and time. Late or missing discussion assignments will affect the
student’s grade.
Understand When You May Drop This Course
It is the
student’s responsibility to understand when they need to consider disenrolling
from a course. Refer to the dates and deadlines for registration. After this
period, a serious and compelling reason is required to drop out of the course.
Incomplete Grade
Policy
Under
emergency/special circumstances, students may petition for an incomplete grade.
An incomplete will only be assigned if there is an acceptable reason, for
example, due to sickness. All incomplete course assignments must be completed
within semester 1.
Commit to Integrity
As a student
in this course (and at this university) you are expected to maintain high
degrees of professionalism, commitment to active learning and participation in
this class, and also integrity in your behavior in and out of the classroom.
Academic Dishonesty Policy
- Academic
dishonesty includes such things as cheating, inventing false information
or citations, plagiarism, and helping someone else commit an act of
academic dishonesty. It usually involves an attempt by a student to show
possession of a level of knowledge or skill that he/she does not possess.
- Course
instructors have the initial responsibility for detecting and dealing with
academic dishonesty. Instructors who believe that an act of academic
dishonesty has occurred are obligated to discuss the matter with the
student(s) involved. Instructors should possess reasonable evidence of
academic dishonesty. However, if circumstances prevent consultation with
student(s), instructors may take whatever action (subject to student
appeal) they deem appropriate.
- Instructors
who are convinced by the evidence that a student is guilty of academic
dishonesty shall assign an appropriate academic penalty. If the
instructors believe that academic dishonesty reflects on the student's
academic performance or the academic integrity in a course, the student's
grade should be adversely affected. Suggested guidelines for appropriate
actions are: -an oral reprimand in cases where there is reasonable doubt
that the student knew his/her action constituted academic dishonesty; -a
failing grade on a particular paper, project, or examination where the act
of dishonesty was unpremeditated, or where there were significant
mitigating circumstances; -a failing grade in the course where the
dishonesty was premeditated or planned.
- The
instructors will file incident reports with the Dean of Academic Affairs
and for Student Affairs or their designees. These reports shall include a
description of the alleged incident of academic dishonesty, any relevant
documentation, and any recommendations for action that he/she deems
appropriate.