Delivery: Self-paced online, 6 hours of pre-recorded lectures with self-assessment quizzes
(not graded) and a multiple-choice final exam (graded).
Credentials: A Introduction to Probability and Statistics digital badge will be issued to students
who pass the exam, and participants will be able to download and print a 91社区
University-issued certificate of course completion.
Who can take this course: This course is intended for all engineers, professionals, faculty, and students.
ABOUT THE COURSE
Introduction to Probability and Statistics Badge
This course teaches the foundational concepts of data analytics, that is, the fundamentals
of probability and statistics. Data science is a growing field of study and practice
as data is quickly becoming the world's most abundant and untapped resource. Social,
mobile, and the proliferation of interconnectivity via the internet have led to vast
amounts of data; however, we all require the ability to transform this raw data into
meaningful information to help make better and faster decisions. Introduction to Probability
and Statistics provides the class participant with the means to convert several forms
of data into usable information.
COURSE OUTLINE
The course will be delivered via 6 hours of pre-recorded lectures. Students will receive
support via virtual office hours and email with the instructor and teaching assistant.
A take-home exam will be distributed and graded, and a course certificate and a digital
badge will be issued to passing students (a grade of 70% or above)
Session 1 - Course Introduction, Course Outline, Fundamentals of Problem Solving, Introduction
to Statistics, Sampling Process, Introduction to Minitab
Session 2 - Basic Statistics: Measures of Location, Measures of Variability, Data Visualization,
Coefficient of Variation, Dot Plot, Histogram, Stem And Leaf, Box Plot
Session 3 - Basic Statistics: Random Distribution, Variable Types, T test, Z test, Statistical
Tables, Confidence Intervals for Mean, Confidence Interval for Proportions, Confidence
Interval for Standard Deviation
Session 4 - Advanced Statistics: Compare Means, Compare Variances, Compare Proportions, Rejection
Region, Fail to Reject, Type 1 error and Type 2 error, Power and Sample Size, P-value
THE INSTRUCTOR
Mohammad T. Khasawneh
Mohammad T. Khasawneh
SUNY Distinguished Prof; School Director; Healthcare Systems Engineering / Health
Systems / Manhattan Graduate Program Director; SUNY Distinguished Professor; Director
School of Systems Science and Industrial Engineering; Watson Institute for Systems
Excellence (WISE)
Mohammad Khasawneh is a SUNY distinguished professor and chair of Systems Science
and Industrial Engineering at 91社区. He received his PhD in industrial
engineering from Clemson University in August 2003 and his BS and MS in mechanical
engineering from Jordan University of Science and Technology, in 1998 and 2000, respectively.
Khasawneh鈥檚 research is focused on healthcare systems engineering, operations management,
and data science. He serves as the director for the Watson Institute for Systems Excellence
(WISE), an institute for advanced studies that generates $2.5-3 million in research
funds annually. In addition, he is the founding director of the Healthcare Systems
Engineering Center, an organized research center (ORC) at 91社区.
Since 2003, Khasawneh has been leading a wide spectrum of projects with U.S. hospital
systems that focus on applied research in the area of healthcare systems engineering.
More specifically, his research is focused on the novel application of systems engineering
to transform healthcare systems into high-performance environments that produce better
patient outcomes at lower costs. His work is applied in ways that lead to optimal
healthcare, including more efficient use of hospital resources; better outpatient
scheduling; streamlined patient flow; improved patient satisfaction; reduced hospital-acquired
conditions (such as infections and patient falls) through predictive analytics; and
improved clinical, operational and financial performance using advanced data science
methods.His health systems engineering center generates over $1 million annually in
sponsored research from various healthcare and hospital systems.
Building on a successful research program and partnerships with health systems around
the country and an academic concentration/minor, at the graduate/undergraduate levels,
Khasawneh developed a 12-month Executive Master of Science with a Health Systems Concentration,
which has been offered in Manhattan since 2013. He has also been instrumental in developing
a new MS degree program in Healthcare Systems Engineering.
Over the years, Khasawneh presented his research at various national and international
conferences, including China, India, Mexico, Jordan, Korea, Thailand, Japan, Turkey,
Indonesia, and Canada. His research activities thus far have led to 60-plus refereed
journal articles, 120-plus conference articles, one patent and three new invention
disclosures. In addition, his sponsored research efforts thus far have resulted in
over $15 million in external funding and over $39 million in software/equipment grants.
In 2006, Khasawneh received a U.S. Air Force Summer Faculty Fellowship to evaluate
the use of multi-sensory cues to improve the landing of unmanned aerial vehicles.
In 2009, he received another fellowship from the U.S. Air Force Office of Scientific
Research to design ergonomic computer workstations for very large displays. He received
the State University of New York (SUNY) Chancellor鈥檚 Award for Excellence in Teaching
in 2011, the University Award for Outstanding Graduate Director in 2015, the University
Award for Excellence in International Education in 2016, and the SUNY Chancellor鈥檚
Award for Excellence in Scholarship and Creative Activities in 2021. He is a member
of the Alpha Pi Mu and Alpha Epsilon Lambda honor societies.
Khasawneh also holds Diplomate status with the Society for Health Systems (SHS), a
professional society within the Institute of Industrial and Systems Engineers (IISE)
that supports the industrial engineering profession and individuals involved with
improving quality and productivity within healthcare. More recently, Khasawneh was
also recognized as an IISE Fellow, the highest classification of the IISE membership.
He also holds an honorary visiting professor position with the Industrial Engineering
Department at Hebei University of Technology in Tianjin, China, and Vellore Institute
of Technology in Vellore, India.
In 2022, Khasawneh was named a SUNY distinguished professor, the highest faculty rank
that SUNY awards. It is reserved for those who have achieved national or international
prominence and an exemplary reputation within their discipline.
Education
BS, MS, Jordan University of Science and Technology
PhD, Clemson University
Research Interests
Healthcare systems engineering
Operations management
Advanced analytics
Awards
University Award for Excellence in International Education, State University of New
York (2015-2016)
University Award for Outstanding Graduate Director, State University of New York (2014-2015)
Chancellor鈥檚 Award for Excellence in Teaching, State University of New York (2010-2011)
COURSE FEES
$250: Standard Rate
$150: BU and SUNY faculty/staff/BU Alumni (graduated May 2020 or before)/Non SUNY
Students
$95: BU and SUNY students and recent BU Alumni (graduated in Dec 2020 or after)/High
School Students
$105: Non-BU and Non-SUNY students (must prove enrollment at another University/College)
$35: Retake Fee Students (we will verify previous registration)
$50: Retake Fee Non-Students (we will verify previous registration)
CANCELLATIONS AND REFUNDS
Please note our cancellation and refund policy: All cancellations must be received
in writing (email) to the Office of Industrial Outreach. All refunds will be assessed
a 10% administrative fee. No refunds for cancellations or non-attendance will be given
after you have started the course. Submit your cancellation request to EMAIL: wtsnindy@binghamton.edu.
If the course is canceled, enrollees will be advised and receive a full refund.
