Teaching Portfolio_Hemalika Abeysundara

Teaching Portfolio
Hemalika T.K. Abeysundara,
Department of Statistics & Computer Science
University of Peradeniya
2015

1 Hemalika T.K. Abeysundara | University of Peradeniya
Dear Reader,
I am Hemalika T.K. Abeysundara, a senior lecturer in Statistics in the Department of Statistics and
Computer Science at University of Peradeniya, Sri Lanka. This teaching portfolio is a representation of
the progress in my teaching over the past ten years and the steps I have taken to improve as an
educator.
To keep it easier to follow my teaching portfolio, I have divided it into five sections: my teaching
philosophy, teaching responsibilities and strategies, evaluations of teaching, contributions to institution
and profession and steps taken toward professional development in teaching. Sample syllabi,
assignments and evaluation schemes are included in the appendix. Please use the table of contents to
navigate through the Portfolio.
To review highlights of the portfolio, refer to my teaching philosophy on page 03, teaching and
mentoring experience on page 06, reflective syllabus on page 13 and comprehensive class feedback on
page 22.
This portfolio has allowed me to express myself through reflection. For added clarity, all the reflective
thoughts and comments on my teaching are printed in green italics throughout the portfolio.
I would like to thank you for taking the time to read my letter. I hope that you enjoy the rest of my
portfolio and learn more about me and my journey.
Sincerely,
Hemalika T.K. Abeysundara, PhD
Department of Statistics & Computer Science,
Faculty of Science,
University of Peradeniya, Peradeniya,
Sri Lanka.
Preface

Preface .......................................................................................................................................................... 1
Table of Content ........................................................................................................................................... 2
Teaching Philosophy ..................................................................................................................................... 3
Teaching Responsibilities & Strategies ......................................................................................................4-6
Undergraduate and graduate teaching..................................................................................................... 4
Teaching Methods..................................................................................................................................... 5
Undergraduate and graduate advising ..................................................................................................... 6
Course and curriculum development ....................................................................................................... 6
Evaluation of Teaching...............................................................................................................................7-8
Student Evaluations .................................................................................................................................. 7
Peer Review............................................................................................................................................... 8
Contributions to institution or Profession.................................................................................................... 9
Steps taken toward professional development in teaching....................................................................... 10
Appendix
Sample Syllabus I................................................................................................................................I-IV
Sample Syllabus II (Distance Learning) .......................................................................................... V-VIII
Sample Examination Paper...............................................................................................................IX-X
Sample Practical Assignment...............................................................................................................XI
Recommendations for teaching..........................................................................................................XII
Table of Content

I firmly believe that I fell in love with teaching because of my mother, who was a secondary school
Geography and History teacher for thirty years. I was inspired by her dedication and commitment
towards helping others as an educator. Throughout her teaching career, I have witnessed the passion
and satisfaction she took in teaching and how she was loved by her students. Having my mother as the
role model, I started following her footsteps from the very first touch of opportunity I got as a teacher.
My ultimate goal is to be the most effective teacher I can be. I want to guide my students to succeed not
only in course work but also in the society after they leave the university. In order to be a successful
educator, I have included five main goals in my teaching philosophy: thorough preparation, balancing
between theory and practice, accommodating active learning environment, inspiring critical thinking
and welcoming evolving teaching strategies to my current practice to improve as an educator.
I trust that planning is the key to success as a distributor of knowledge. Therefore, I allocate a
considerable amount of time and effort on preparation for my class. I use lesson plans to organize the
class and make sure the content is accurate and well supported with relevant examples.
As a statistics instructor, I always try to complement the theoretical concepts with real-life examples. I
believe that teaching should not be limited to textbook content but should also provide information
with real-world applications so that students can understand more concretely what they are learning.
Since Statistics is a science that is utilized in every field, I emphasize how they can apply theoretical
concepts in many other fields. Therefore, I always accompany examples and exercises related to
biological sciences, social sciences and Business.
My teaching methods are more towards student centered learning as it simulates the learning process. I
provide opportunities for my students to actively participate in class. The assignments and in-class work
are mainly focused on extracting knowledge, by students themselves, under my supervision. I encourage
my students to search for knowledge, based on what they have learned in class. By providing extra
resources and links, I guide them to seek beyond the course work.
Education is also powered by new technology and strategies. In addition to available teaching resources,
I always try to combine new approaches to my teaching methods. Students of the new generation is
more attached to technology and I am trying to use that as an advantage as an educator. Whenever I
see an opportunity, I attend workshops and programmes to improve my teaching methods so that I can
reach one step closer to become an effective teacher.
Teaching Philosophy

Undergraduate and Graduate Teaching
During the ten year period as a teacher, I have gained experience in conducting undergraduate and
graduate courses both locally and internationally. I have conducted face-to-face classes and also
distance learning (online) courses. Following are the teaching responsibilities I have held in chronological
order.
Position Institute Period
Temporary Lecturer
University of Peradeniya, Peradeniya, Sri Lanka
2005 June-
2007 November
Graduate Teaching Assistant
Department of Mathematics & Statistics,
Texas Tech University, TX, USA
2008 January-
2014 June
Lecturer
Department of Mathematics & Statistics,
Texas Tech University, TX, USA
2014 August-
2014 December
Senior Lecturer
2015 January-
Up to date
Lecturer
Post Graduate Institute of Science,
2015 April-
Up to date
I have conducted both Statistics and Mathematics courses for students who are majoring the subject
and also for those who are non majors. I find it more challenging when it comes to teaching Statistics
and Mathematics for students from other disciplines, because I have to make them interested in the
subject prior to teaching the actual content of the course.
I have listed selected courses I have conducted in recent five years at Texas Tech University.
• Statistical Methods (MATH2300 and MATH2300 Distance Learning)
3 credits, 80-100 students per semester
• Mathematical Statistics for Engineers & Scientists (MATH3342)
• Pre- Calculus (MATH1550)
• Business Calculus (MATH1331)
For each of the above courses I was responsible for teaching the course content, preparing assignments,
tutorials, quizzes and mid semester examinations. The final examinations are prepared by the course
coordinator except for MATH 3342 and I was responsible for grading all the assignments.
Teaching Responsibilities and Strategies

Following are the undergraduate courses I currently conduct at University of Peradeniya.
• Introduction to Probability Theory (ST/MT102)
• Probability Theory (ST201, a continuation of ST/MT102)
• Statistical Simulation (ST205)
• Survival Analysis & Reliability Theory (ST408)
3 credits, 20 students per semester
In addition to conducting undergraduate courses, I am an appointee to the panel of teachers/examiners
of the PGIS (Postgraduate Institute of Science) and I conduct following courses for MSc. Programme in
Applied Statistics and MSc. Programme in Disaster Management.
• Statistical Methods (Preliminary Course) – SC403, 30 lecture hours
• Sampling Techniques – SC505, 30 lecture hours
• Statistical Applications –ESD405, 15 lecture hours
Teaching methods
In my face-to-face classes I use a blend of lecture, discussion and problem solving. Students are actively
encouraged to contribute to discussions and learning activities. I make frequent use of learning projects
which students are grouped to explore issues. During my teaching in the USA, I learned that diverse
classrooms produce rich solutions.
Since Statistics is a practical subject based on a firm theoretical background, after explaining the theory,
I show students how it can be applied in real world scenarios. I encourage students to be skilled in a
collection of statistical software, and include practical sessions to guide them. Since practice is the key
to success in mathematics related subjects, I provide a considerable number of tutorials and in-class
assignments to improve problem solving and analytical skills.
The distance learning classes are challenging in the sense of communication between students and
teacher. Specials procedures have to be implemented in order to maintain credentials and
communications. I used text books facilitated with online homework and quiz submission systems while
course materials are provided in the course homepage. Examinations are held at selected examination
centers and student answers are collected via electronic mails as scanned documents. I was responsible
in maintaining online assignments in timely manner, solving any technical problems while effectively
communicating with students via electronic mails. Examination centers selected by students are
checked by the university administration.
Please see the appendix for selected syllabi and special instructions provided for the above courses.

Undergraduate and Graduate Advising
I act as the supervisor for 4-5 undergraduate students who are following the special degree in Statistics.
I guide them with proposal writing, literature review, data analysis techniques, report writing and
presentation skills. After the completion of an effective research work, I direct them to publish their
findings. My role as an advisor focuses mainly on steering my students towards better research ethics
and also on improving writing and presentation skills.
Currently I am advising one M.Sc. student and co-advising one M.Phil. student.
Course and Curriculum Development
I actively involve in designing new courses and revising existing courses conducted by the Department of
Statistics and Computer Science as a member of the Curriculum Development Board of the Faculty of
Science. I am currently in the process on developing a new M.Sc. programme: M.Sc. in Computational
Statistics for the PGIS.

Student Evaluations
Student evaluations are vital to my effort to improve my teaching methods. I collect feedback from my
students soon after finishing the mid semester examination so I can pay attention to their requests and
progress my teaching style for that course. The university collects student reviews each semester and I
use them to correct any negative feedback.
Following is a summary of student evaluations I have received during 2012 and 2013. The scores are in
5.0 - scale averaging over all participated students.
Course: MATH3342 Fall – 2012 and MATH3342D01 (Distance Learning)- Fall 2013
Response Score-
MATH3342
Score-
MATH3342D01
Overall this instructor was effective 4.71 4.75
The instructor was available for consultation during office hours
or by appointment
4.57 4.63
The instructor simulated student learning 4.49 4.63
The instructor treated all students fairly 4.82 4.88
The instructor treated all students with respect 4.84 4.88
The instructor welcomed and encouraged questions and
comments
4.73 4.88
The instructor presented the information clearly 4.64 4.75
The instructor emphasized the major points and concepts 4.66 4.75
The instructor went beyond presenting the information in the
text
4.58 4.38
The instructor demonstrated the knowledge of the subject 4.80 4.75
https://appserv.itts.ttu.edu/CourseEvaluation/Result.aspx
Here are some anonymous comments by students in M.Sc. in Applied Statistics:
“Very useful to memorize basic statistics. Teaching methods are good”
“Great in delivering lectures. Very simple, very energetic”
“You are the basic eye opener for us. Interesting period we had”
“This class is very helpful. I got the extra idea about Statistics”
“We can easily understand what you taught. Your teaching ability is very good and very interesting
lectures”
Evaluations of Teaching

Peer Review
I have being reviewed by my colleagues and professors many times during my teaching career. I have
received positive comments from many of them and valuable suggestions to improve my teaching
methods.
Here is a part of recommendation I have received and the full letter is available in appendix.

• Annual Statistics Camp.
The Statistical Society of University of Peradeniya organizes an annual Stat Camp to promote
practical aspects of Statistics among students. As an academic member of the department I
actively involve in designing the program and organizing materials and resource persons.
Stat Camp is mainly focused in upholding knowledge and skills of students in an environment
outside the class room. The two day camp is usually conducted at Sanasa Campus, Kegalle and
academic staff members from other state universities are also invited to share their knowledge
and experience with our students. Students are evaluated on skills such as team work, time
management and applying theory to practice. The Stat Camp is a student centered learning
experience as a whole.
• Workshops and competitions at University of Peradeniya to promote Statistics.
I support my institute, the Department of Statistics & Computer Science to promote Statistics
via organizing competitions and workshops. By guiding my students toward research and
projects, I contribute the University of Peradeniya to achieve its goal of producing skilled
graduates.
• Conducting workshops in collaboration with other state universities and schools by invitation.
Whenever invited by other state universities and schools in Sri Lanka I always come forward to
share my knowledge as a resource person. Since Statistics is a demanding subject with less
resource persons for newly established universities, I contribute to my profession by providing
service as a resource person. I keenly participate in workshops conducted at schools in order to
promote Statistics among advance level students.
• Statistical Consultation
Although teaching is the main focus as an educator, I help researchers from other disciplines
with data analysis part of their research work. I work as the statistician for the Center for
Education, Research and Training for Kidney Diseases (CERTKid) at Faculty of Medicine,
University of Peradeniya. I conduct sessions on statistical concepts for the team members and
guide them on statistics related problems throughout their research work. It has given me the
opportunity to serve as an educator at the national level.
Contributions to Institution or Profession

I believe that developing my teaching strategies is essential to become an effective educator. Following
are the programmes I have participated during my journey as a teacher.
• International Teaching Assistant Workshop (2008)
Since I was an international student, Texas Tech University required all potential international
instructors to not only attend the three weeks international teaching assistants (ITA) workshop,
but also pass an oral exit interview by the Foreign Language Department. I excelled at the oral
exam and thus, was approved to teach.
I was trained in speaking, voice control and classroom management guidelines in this workshop
followed by video taping a class room teaching. The workshop helped me immensely to survive
as an international teacher among a divers student community.
• The Groundwork Program: Teaching Training for Graduate Students (2014)
The Teaching, Learning and Professional Development Center of Texas Tech University
conducted the workshop which I was trained specially on handling new generation students,
blackboard management, and advance technology for teaching and managing bigger
classrooms.
The second video tape of my teaching was covered in this session and I was pleased to see the
improvements in my teaching since the first one.
• Induction Programme - Staff Development Center (2015)
The most recent opportunity I had on developing my carrier is the induction programme
conducted by the Staff Development Center of University of Peradeniya. It provided valuable
experience on improving my teaching and geared me up towards an effective educator.
Steps Taken Toward Professional Development in Teaching

Appendix - Sample Syllabus I
I
MATH 2300-002 Statistical Methods, Fall - 2009
MWF 8.00 am – 8.50 am, MA 110
Instructor Information: Hemalika Abeysundara
E-mail : hemalika.abeysundara@ttu.edu
Office: MA 117F
Office Hours: MWF 9.00 am - 10.00 am
MWF 11.00 am - 12.00 noon or by appointment
Course Coordinator Information: Dr. Byungtae Seo
E-mail : byungtae.seo@ttu.edu
Phone : 742-2580x269
Office: MA 215
Course Information:
This course gives the students an introduction to some of the basic statistical methods used in
practice
Text Book: STATISTICS: The art and science of learning from data, 2nd
Edition by Agresti
and Franklin
Prerequisite: MATH1320 or the equivalent
Course Outline:
Chapter 1 – 1.1 - 1.3
Chapter 2 – 2.1 - 2.6
Chapter 3 – 3.1 - 3.4
Chapter 4 – 4.1 - 4.3
Chapter 5 – 5.1 - 5.4
Chapter 6 – 6.1 - 6.3
Chapter 7 – 7.1 - 7.3
Chapter 8 – 8.1 - 8.4
Chapter 9 – 9.1 - 9.4
Chapter 10 – 10.1 – 10.2
Chapter 11 – 11.1 - 11.2
Methods of Assessment of learning Outcomes:
The expected learning outcomes for this course will be assessed through one or more activities such
as exams, in class practice problems, quizzes, class discussions, board work, home work assignments
and other optional activities deemed appropriate by the instructor. Points will be given for the
performance in class. It is important to note that all of these assessments are for your learning benefits
but NOT all of them will affect your grade.
Grading and Scale:
The course grade will be determined by each method of assessment weighted as follows.
Quizzes and Homework:
Assessment Percentage
Home work 15%
Quizzes 15%
Mid term tests 30%
Final exam 35%
Attendance 5%
Final Percentage Grade
90-100 A
80-89 B
70-79 C
60-69 D
59 and below F

II
Quizzes will be given on every other Wednesday, starting from 9th
of September and pop-up quizzes
may be given on any day during the class and won’t be announced in advance. Completed homework
must be submitted on due date.
Expected Learning outcomes:
MATH2300 satisfies the university core curriculum requirements in Mathematics: “students
graduating from Texas Tech University should be able to demonstrate the ability to apply
quantitative and logical skills to solve problems.” It meets the TTU general education student
learning outcomes for mathematics that students will
 Be able to apply arithmetic, algebra, geometry and statistics to solve problems.
 Be able to represent and evaluate basic mathematical information numerically, graphically and
symbolically.
 Be comfortable with interpreting mathematical models such as formulas, graphs, tables and
schematics and draw inferences from them.
Students will learn the meaning of, and computational procedures related to the elementary statistical
concepts used by the general population decision making.
In particular the students will
 Develop proficiency in solving real-world problems.
 Compute various statistical measures, including the mean, median, mode, standard deviation,
variance and quartiles.
 Utilize graphical representations of data.
 Solve problems involving the binomial and normal distributions.
 Apply the Central Limit Theorem.
 Compute and interpret confidence intervals.
 Conduct and interpret hypothesis tests.
 Use linear regression models.
 Learn to think logically and to gain confidence in their ability to understand and enjoy
statistical applications.
 Be able to demonstrate on quizzes and tests that they have mastered the above objectives.
Attendance:
 Class attendance is very important to success in this course. Roll will be taken at every class
meeting. Students with less that 3 missed classes for the entire semester will receive a bonus
of 5 points.
 Absence due to religious observance (OP 34.19) - The Texas Tech University Catalog states
that a student who is absent from classes for the observance of a religious holy day will be
allowed to take an examination or complete an assignment scheduled for that day within a
reasonable time after the absence (p.49). Notification must be made in writing and delivered
in person no later than the 15th class day of the semester.
 Absence due to officially approved trips – The Texas Tech University Catalog states that the
person responsible for a student missing class due to a trip should notify the instructor of the
departure and return schedule in advance of the trip. The student may not be penalized and
responsible for the material missed. (p.49)
Missed Work:
Makeup examinations can be taken for any missed class tests. The student is responsible for making
necessary arrangements to take the make-up test within one week after returning to the schools. There

III
will be no make-ups for quizzes unless the student provides a valid reason for the absence which
includes:
 The student is out of town performing duties on behalf of the TTU (Eg: Athletics)
 Religious holiday (OP 34.19)
 Severe illness which is documented by a physician.
 Immediate family death
 Other extenuating circumstances, at the instructor’s discretion.
Important Days:
Student-Initiated Add/Drop on the Web Aug 27
Last day to add a course Sep 01
University Holiday (Labor Day) Sep 07
Class Test I Oct 02
Student Holiday Oct 12
Mid Semester Grade Due Oct 26
Final Day to Drop a Course Nov 02
Class Test II Nov 23
Thanks Giving Holiday Nov 25- 29
Period of no Exams Dec 03- 09
Last Day of Classes Dec 09
Final Comprehensive Exam Dec 11, 10.30 AM – 1.00 PM
[Location to be announced]
Academic Integrity:
 Academic misconduct
“It is the aim of the faculty of Texas Tech University to foster a spirit of complete honesty and a high
standard of integrity. The attempt of students to present as their own any work that they have not
honestly performed is regarded by the faculty and administration as a serious offense and renders the
offenders liable to serious consequences, possibly suspension.”
[Texas Tech University Catalog (p.49) and (OP 34.12)]
 Civility in the Classroom
Students are required to be in the class on time and they should not leave the class unless for a valid
reason. Any appearance to the class later than 15 minutes should be notified to the instructor in
advance. Using mobile phones in class is NOT ALLOWED.
ADA Accommodation:
Any student who because of a disability may require special arrangements in order to meet course
requirements should contact the instructor as soon as possible to make any necessary
accommodations. Student should present appropriate verification from AccessTECH. No requirement
exists that accommodations be made prior to completion of this approved university procedure. For
additional information, you may contact the Student Disability Office at 335, West Hall or 806-742-
2405

IV
Steps toward success in Statistics:
Statistics is a process of collecting, analyzing and interpreting data. It is a practical subject based on
various methods and procedures. To succeed in this course, a student should
1. Attend class every day.
2. Read the text book.
3. Take notes in class.
4. Do assigned homework.
5. Get help immediately when needed.
6. Review regularly.
Disclaimer:
This syllabus provides a general plan; deviations may be necessary.

Appendix - Sample Syllabus II (Distance Learning)
V
MATH 3342 Online Section – Fall 2013 – Mathematical Statistics for Engineers & Scientists.
Instructor Information: Hemalika Abeysundara
E-mail: hemalika.abeysundara@ttu.edu (preferred method of communication)
Office: MA 003C
Office Hours: Tuesday 10.00 am-1.00 pm or by appointment. In addition, we can communicate via email.
There are multiple technology options that allow me to provide detailed explanations to your questions.
Course Coordinator: Dr. James Surles
E-mail: james.surles@ttu.edu
Office: MA 203
Prerequisite: MATH 2350 or 2450
Class Times: Online at www.webassign.net . Course ID: ttu48414765.
Enter code from textbook. If the textbook is used and does not have a valid code, you can purchase a
code from www.webassign.net when you register. Quick student guide for registration is attached
separately.
Textbook: Probability and Statistics for Engineering and Sciences, 8th
Edition by Jay .L. Devore
[ISBN-13:978-0-538-73352-6]
Textbook Options (All 3 options include access to the electronic version of the book)
1. Purchase a new physical book that includes a pre-paid web access code.
(physical book and e-book)
2. Purchase a used book, then purchase the web access code directly from www.webassign.net .
(physical book and e-book)
3. Do not purchase a physical book, purchase the web access code directly from www.webassign.net .
(no physical book; only e-book)
Required Tools: Scientific calculator and internet access.
Course Outline: August 26th
– December 04th
August 26 – September 15 Chapters 1, 2 (Quiz 1)
September 20 – October 13 Chapters 3, 4 (Quiz 2)
Proctored Mid-Term Exam (Ch 1 – 4) Must be completed by Friday, October 18th
October 25 – November 12 Chapters 6, 7 (Quiz 3)
November 19 – December 03 Chapters 8, 9 (Quiz 4)
Proctored Final Exam (comprehensive) Must be completed by Friday, December 11
You are always welcome to and encouraged to complete the assignments, quizzes, and exams before their
due dates. The due dates listed are the absolute deadlines.
Expected Learning Outcomes:
Students will apply their calculus knowledge to learn the meanings of, and computational procedures
relating to, basic statistical concepts used for making decisions in the sciences and engineering. In
particular, students will
 Understand the need to be wary of statistical claims, common pitfalls in sampling, and
misrepresentation of conclusions
 Understand the meanings of various statistical measures, including the mean, median, mode,
standard deviation, variance, and quartiles

VI
 Become familiar with various graphical representations of data and learn to recognize misleading
graphs.
 Develop proficiency in real-world probability problems
 Understand the concept of a probability distribution and real-world problems involving various
distributions, including Binomial, Normal, Hypergeometric, and Poisson distributions
 Understand and apply the Central Limit Theorem
 Compute and interpret confidence intervals
 Conduct and interpret hypothesis tests
 Understand linear regression models
Learning Assessment Components:
The expected learning outcomes for the course will be assessed through: exams, quizzes and homework
assignments.
All homework assignments and quizzes will be administered through the course’s website www.webassign.net .
The Course ID is ttu48414765. Instructions for registration are found in a separate pdf file.
Payment codes are available with the purchase of the textbook. You will need to make sure you purchase a textbook
with an active payment code. Otherwise, you will need to purchase an online payment code. The instructions for
purchasing the payment code separate of the book are found at the website.
 Homework: Homework is assigned on the course website for each chapter. Each online-homework
assignment will be graded automatically by the website. You are always free to attempt more problems from
the book for more practice and the “similar problems” provided as links in the homework assignments. The
online-homework assignments allow up to 3 attempts per problem – accepting the best of the three attempts.
The problems will remain on the site for the full semester so that you can review them for exams.
 Quizzes: There are 4 quizzes in the course. The quizzes will not be available to open until the homework
assignments have been completed for the chapters the quizzes cover. The quizzes are timed. They are not
proctored. Once you start the quiz it must be completed within the time allowed.
 Exams: There will be 2 Proctored exams during the semester: a Mid-Term that covers Chapters 1–4 and a
Final Exam that covers all the chapters at the end of the semester. The Mid-Term and Final Exam must be
proctored and completed by the dates listed above in the “Course Outline.” An “Exam Form” will be emailed
out at the beginning of the semester so you can inform me if you are in the Lubbock area (thus taking the
Mid-Term and Final Exams with me at Texas Tech) or if you are outside of the area (thus choosing an
appropriate proctor and providing the requested information about the proctor).
The course grade will be determined by each method of assessment weighted as follows.
No extra credit is provided in this class.
Sections Covered:
Assessment Percentage
Home work 20%
Quizzes 25%
Mid Term Test 30%
Discussion 5%
Final Exam 25%
Final Percentage Grade
90-100 A
80-89 B
70-79 C
60-69 D
59 and below F

VII
Quiz 1 Quiz 2 Quiz 3 Quiz 4
Ch 1.1 – 1.4 Ch 3.1 – 3.4, 3.6 Ch 6.1 Ch 8.1-8.5
Ch 2.1,2.2, 2.4,2.5 Ch 4.1 – 4.5 Ch 7.1 – 7.4 Ch 9.1-9.5
Preparation for Class:
You are expected to keep up with the schedule set forth by the due dates of the homework assignments, quizzes and
the exams. Reading the book is paramount along with practicing the homework assignments. Homework problems
are available for practice through the assigned material, through the website’s study plan, and at the end of each
section in the book. The Texas Tech University Catalog states that students are expected to spend approximately two
hours in preparation for each hour of lecture.
Academic Integrity:
“It is the aim of the faculty of Texas Tech University to foster a spirit of complete honesty and a high standard of
integrity. The attempt of students to present as their own any work that they have not honestly performed is regarded
by the faculty and administration as a serious offense and renders the offenders liable to serious consequences,
possibly suspension.”
Important Dates:
Last day to add a course Aug 29
Labor Day – University Holiday Sep 02
Proctored Mid term Test Oct 18
Mid Semester Grade Due Oct 21
Final Day to Drop a Course Oct 28
Thanksgiving Holiday Nov 27- Dec 1
Final Comprehensive Exam To be announced
Students with Disabilities:
Any student who, because of a disability, may require special arrangements in order to meet the course requirements
should contact the instructor as soon as possible to make any necessary arrangements. Students should present
appropriate verification from Student Disability Services during the instructor’s office hours. Please note:
instructors are not allowed to provide classroom accommodations to a student until appropriate verification from
Student Disability Services has been provided. For additional information, you may contact the Student Disability
Services office in 335 West Hall or 806-742-2405.
Absences:
Absences should not be much of an issue in this course. If you must be away from your studies and it conflicts
with a due date, the best option is to adjust your study schedule to complete the assignment, quiz, or exam
before the due date. Otherwise, you need to discuss any conflicts with me in advance of any due date.
Absence due to Religious Holidays: The Texas Tech University Catalog states that a student shall be excused
from attending classes or other required activities, including examinations, for the observance of a religious holy
day, including travel for that purpose. A student who intends to observe a religious holy day should make that
intention known in writing to the instructor prior to the absence. A student who is absent from classes for the
observance of a religious holy day shall be allowed to take an examination or complete an assignment scheduled
for that day within a reasonable time after the absence. (p.57)
Absence due to Officially Approved Trips: The Texas Tech University Catalog states that the department
chairpersons, directors, or others responsible for a student representing the university on officially approved trips
should notify the student’s instructors of the departure and return schedules in advance of the trip. The instructor so
notified must not penalize the student, although the student is responsible for material missed. Students absent

VIII
because of university business must be given the same privileges as other students (e.g., if other students are given
the choice of dropping one of four tests, then students with excused absences must be given the same privilege).
(p.57)
Excused/Unexcused Absences: Whether an absence is excused or unexcused is determined solely by the instructor
with the exception of absences due to religious observance and officially approved trips described above. In case of
an Illness that will require absence from class for more than one week, the student should notify his/her academic
dean. The dean’s office will inform the student’s instructors through departmental office. In case of absences because
of a brief illness, the student should inform the instructor directly.
Illness and Death Notification: The Center for Campus Life is responsible for notifying the campus community of
student illnesses, immediate family deaths and/or student death. Generally, in cases of student illness or immediate
family deaths, the notification to the appropriate campus community members occur when a student is absent from
class for four (4) consecutive days with appropriate verification. It is always the student’s responsibility for missed
class assignments and/or course work during their absence. The student is encouraged to contact the faculty member
immediately regarding the absences and to provide verification afterwards. The notification from the Center for
Campus Life does not excuse a student from class, assignments, and/or any other course requirements. The
notification is provided as a courtesy.
Disclaimer:
This syllabus provides a general plan; deviations may be necessary.

Appendix - Sample Examination
IX
UNIVERSITY OF PERADENIYA
DEPARTMENT OF STATISTICS AND COMPUTER SCIENCE
END SEMESTER EXAMINATION, SEMESTER I – June, 2015
ST201 – PROBABILITY THEORY.
Time Allowed: TWO Hours Answer All Questions.
1. The joint Cumulative Density Function (CDF) of the two random variables X and Y is given as
a). Find the joint probability density function (pdf) and the marginal pdfs of X and Y.
b). Find
c). If another random variable U is defined as , find the pdf of U.
2. Suppose X and Y are two random variables with means E(X) and E(Y) respectively.
a). In the usual notation, show that
b). Suppose the joint pmf of X and Y is;
(x,y) (1,1) (1,2) (2,1) (2,2)
f(x,y) 3/8 1/8 1/8 3/8
Find
3. Let be a random sample from a Uniform [0, θ] distribution. Let .
a). Derive the CDF and the pdf of .
b). Show that .

Appendix - Sample Examination
X
4. Let the random variables and have the joint probability density function
Suppose and .
a). Find the joint probability density of and .
b). Find the marginal densities of and .
c). Are and independent? Justify.

Appendix - Sample Practice Assignment
XI
Exercise 1 (Graphical Summaries) Date : 01/21/2010
(1) 25 patients were randomly selected from a bunch of heart patients. Then the age of each patient
was recorded.
48, 35, 50, 28, 59, 49, 51, 38, 42, 43, 56, 37, 50, 54, 60, 41, 46, 58, 41, 52, 54, 47, 55, 51, 45
Draw a dot plot for the above data set
(i) What is the most common age (Mode)?
(ii) What is the minimum age?
(iii) What is the maximum age?
(2) Draw the Steam-and-leaf plot.
Step 1: Arrange data in ascending order.
Step2: Use all digits except for the final digit as stem and use final digit as leaf and arrange data on a
vertical line.

Texas Tech University
Department of Mathematics and Statistics
Lubbock, Texas 79409-1042
April 4, 2014
Dear Sir/Madam:
This is a letter of recommendation for Ms. Hemalika Abeysundara who is applying
for a instructor position in our department. Ms. Abeysundara received an M.S degree in
statistics in 2010 at TTU. Her research advisor was Professor Byungtae Seo. In August
2014, she will receive a doctoral degree in mathematics. Her doctoral research advisor is
Professor Frits Ryumgaart.
While studying at Texas Tech University, Ms. Abeysundara was one of my students in
a graduate course on the theory and application of stochastic diﬀerential equations. She
obtained the highest average in the class. I was impressed with her understanding of both
the theoretical and the practical aspects of the material. Ms. Abeysundara has pleasant
personality and a strong work ethic. She is gentle and friendly and I enjoyed having her as
a student.
Finally, Ms. Abeysundara has been a teaching assistant in the Department of Mathe-
matics and Statistics at TTU since 2008. She has taught several courses such as College
Algebra, Statistical Methods, and Mathematical Statistics for Engineers and Scientists.
Several times I was asked to observe and evaluate her teaching. Ms. Abeysundara ex-
plained the material very well. She excelled at the rapport that she had with her students.
The students were always quiet, attentive, and respectful in her classes. Ms. Abeysundara
is an excellent teacher.
Please consider Ms. Hemalika Abeysundara for an Instructor Position in the Depart-
ment of Mathematics and Statistics at TTU. Thank you very much.
Sincerely yours,
Edward J. Allen, Professor of Mathematics
Department of Mathematics and Statistics
Texas Tech University
Lubbock, TX 79409
Phone: (806) 834-1013
E-mail: edward.allen@ttu.edu

Teaching Portfolio_Hemalika Abeysundara

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