Introduction to Probability and Statistics
- Instructor: Dr. Mohammad Khasawneh
- Open year round
- 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 be issued to students who pass the exam and participants will be able to download and print a Binghamton 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
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 most abundant and untapped resource. Social, mobile and the proliferation of interconnectivity via the internet has led to vast amounts of data; however, we all require the ability to transform these 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.
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, Fundamental 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
Dr. Mohammad T. Khasawneh
- Professor and Chair in Systems Science & Industrial Engineering Department
- Associate Director, Watson Institute for Systems Excellence
- Director, Healthcare Systems Engineering Center
- Director, Human Factors and Ergonomics Laboratory
- Graduate Program Director, Executive Master of Science in Health Systems
- SUNY Chancellor's Award for Excellence in Teaching
- PhD, Industrial Engineering, Clemson University
- $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 immatriculation at other University/College)
- $35: Retake Fee Students (we will verify previous regsitration)
- $50: Retake Fee Non-Students (we will verify previous regsitration)
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: email@example.com.
If the course is canceled, enrollees will be advised and receive a full refund.