Page 128 - University Bulletin

BACHELOR OF SCIENCE IN APPLIED STATISTICS AND DATA SCIENCE
(SASCED-P 5420102)

Introduction

Applied Statistics and Data Science is an interdisciplinary field that combines statistical reasoning,
computational techniques, and data-driven methodologies to extract meaningful insights from
complex datasets. This program equips students with the theoretical foundations and practical skills
required to analyze, interpret, and model data for informed decision-making across diverse domains
such as science, business, government, and healthcare. Emphasizing ethical practices, critical thinking,
and lifelong learning, the program prepares graduates to tackle real-world problems and contribute
to data-centric innovation in society.

Vision
The Applied Statistics and Data Science Program aspires to be a leading academic program in the
region, recognized for excellence in statistical education, research, and its contributions to solving
data-driven challenges across industries and society.

Program Mission

The program's mission is to prepare students with statistical and data science knowledge accompanied
by research skills to contribute to society.

Program Goals
● Provide students with knowledge and skills in both statistical modeling and data science for
algorithmic problem solving and scientific discovery.
● Promote professionalism and ethical responsibilities of statistical modeling and data
science toward the community.
● Equip students with lifelong learning and research skills toward a successful career as a
professional or researchers in the field of statistics and data science.

Program Learning Outcomes
Upon successful completion of the Bachelor of Science in Applied Statistics and Data Science,
graduates are expected to be able to:
K1. Understand basic statistical concepts of data analysis, data collection and management,
modeling, and inference.
K2. Demonstrate a depth of knowledge and application of concepts for understanding research
methodology and inquiry techniques.
K3. Apply knowledge of computing in all fields of statistics and data science.
S1. Solve relevant problems from real-world data using critical thinking and creative solutions.
S2. Adapt statistical techniques and software tools and instruments to deal with practical
activities.
S3. Use mathematical operations and quantitative methods to process data and information in
various complex contexts of statistics and data science.
V1. Demonstrate commitment to ethical awareness, academic standards, and professional
values in all aspects of statistics and data science.

116 PSU UNDERGRADUATE BULLETIN