Page 260 - University Bulletin

STAT219 Introduction to Stochastic Analysis
Credits: 3 (3,0,0) Prerequisite: STAT111
The course is tailored specifically to meet the needs of actuarial students who require a strong
foundation in stochastic analysis for their future careers. This course aims to provide actuarial
students with the necessary knowledge and skills to understand and apply stochastic analysis
techniques in actuarial practice, particularly in the areas of risk assessment, insurance modeling,
and financial analysis. Throughout the course, students will delve into key topics such as stochastic
processes, stochastic calculus, and applications in actuarial science. The course will emphasize
both theoretical understanding and practical application, enabling students to develop the
necessary analytical and problem-solving skills required in actuarial work.

STAT271 Statistical Analysis
Credits: 3 (3,0,0) Prerequisites: STAT101
This course offers an in-depth exploration of statistical methods, including multiple regression,
ANOVA, and nonparametric methods, along with time series analysis and the application of index
numbers in economic data. Emphasizing practical skills, it guides students through projects using
statistical software like StatCrunch, R and SPSS, focusing on the application of these techniques
in real-world scenarios. Key topics also cover the properties of good estimators: consistency, and
efficiency. Suitable for those with a foundational understanding of statistics, this course equips
students with the expertise to conduct complex data analyses.

STAT272 Applied Statistics for Engineers
Credits: 3 (3,0,0) Prerequisites: STAT101
The course is designed for engineering problem solving and for development of engineering
applied statistical thinking. The course covers principles of engineering data collection; principles
of experimentation; Confidence intervals and Hypothesis testing for one ,two and multi- sample
studies; Test for Independence, Homogeneity. Simple and Multiple regression analysis and
Interpretations; Analysis of variance. Students employ statistical software (e.g. R) to perform
statistical data analysis.

STAT311 Time Series and Applications
Credits: 3 (3,0,0) Prerequisite: STAT112
Time Series consist of values of a variable recorded in an order over a period of time. Such data
arise in just about every area of science and the humanities, including econometrics and finance,
engineering, medicine, genetics, sociology, environmental science. The course is intended to
prepare the students for methodological research in this area and to train the students on cutting-
edge data analytic methods for a time series. The course will provide a basic introduction to
modern time series analysis. It will cover time series regression and exploratory data analysis,
ARMA/ARIMA models, model identification/estimation/linear operators, Fourier analysis, spectral
estimation, and state space models. The Analyses will be performed using the freely available
packages, such as “astsa” R package, which accompanies the book. Both R and RStudio (or Python)
will be required for this class.

TRN110 Translation Theories
Credits: 3 (3,0,0) Prerequisites: None
This course covers the principle and theory of translation. It covers the history of recent theoretical
development in translation studies through readings from the most important texts in translation
theory. It analyses the major concepts, issues and theories of translation in relation to its historical
context. The course will also assist students in making the connection between translation
theories and practice to ensure effective use of the theories and to make an informed decision in
translation activities.

248 PSU UNDERGRADUATE BULLETIN