Page 163 - University Bulletin

ACSC473 Loss Models
Credits: 3 (3,0,0) Prerequisite: STAT311 and ACSC225
This course offers a comprehensive exploration of insurance, focusing on the distribution of
aggregate claims and the associated risks. Students will analyze variations in expected claim
numbers and amounts, examining frequency and severity distributions, individual and collective
models, ruin theory, continuous-time compound Poisson surplus processes, reinsurance, dividend
formulas, and credibility models. Through simulation exercises, students will gain practical insights
into these concepts. Additionally, the course introduces empirical Bayes methods and statistical
distributions for modeling loss experiences. Emphasizing risk theory, students will assess the
operation of insurance and takaful systems, evaluating data credibility for ratemaking. By the
course's conclusion, students will possess a thorough understanding of insurance risk
management principles and their real-world applications.

ACSC493 Cooperative Education
Credits: 10 (10,0,0) Prerequisite: Department Approval
The aim of this course is to provide students with the opportunity to spend a specified period of
time in local or international companies and institutions, and according to a suggested work plan
of training. The duration of the training is 7 months and carries a 10 credit hours weight. The
evaluation and supervision of the student’s performance is carried out by both the hosting
workplace and the relevant department. Emphasis will be placed on the application of theoretical
knowledge in real-world settings, helping students refine their skills in teamwork, communication,
and project management. By actively participating in cooperative learning environments, students
will gain valuable industry insights, expand their professional network, and enhance their
problem-solving capabilities in the dynamic field of language and media.

ART101 Art Appreciation
Credits: 2 (2,2,0)
This course surveys the development and interrelationship of the visual arts, music and drama,
both classical and contemporary, in selected cultures.

ASDS213 Data Structure and Algorithms
Credits: 3 (3,1,0) Prerequisite: CS102
This course introduces classical data structures and algorithms with emphasis on performance
using asymptotic analysis of algorithms and complexity classes. Fundamental data structure
includes lists, stacks, queues, heaps, trees, and graphs. The student will learn a variety of
algorithms for searching, sorting, traversing and hashing. In addition, the course covers the
application of these data structures and algorithms in real-life problems and implementing them
in modern programming languages.

ASDS225 Statistical Programs
Credits: 3 (3,0,0) Prerequisite: STAT111 and CS102
This course focused on collecting, organizing, and analyzing data to build models and
communicate analytical results in a reproducible manner. Students will use SPSS and R tidyverse
packages to acquire, clean, and tidy data; develop numerical and graphical displays; write basic
functions, and present/communicate their process, findings, and recommendations. The project
has been included to complete an analysis of complex data and communicate the elements of the
analysis and the results in writing and through an oral presentation.

151 PSU UNDERGRADUATE BULLETIN