Dr. Mohammad Rafiqul Islam (RFI)
Associate Professor
Department of Mathematics and Natural Sciences
buX
Elements of Statistics and Probability (MNS)
Enrollment is Closed
STA201: Elements of Statistics and Probability
About STA201
The main objective of the subject is to familiarise students with the basic concepts and tools of statistics and probability. Students will obtain a clear, concise understanding of the fundamental features and methods of statistics and probability along with relevant interpretations and applications. This course demonstrates to students how simple statistical and probabilistic tools can help analyse a wide range of problem in the field of computer science, engineering, natural sciences, economics and business.
Course Instructors
Dr. Asim Kumer Dey
Adjunct Faculty Member
Department of Mathematics and Natural Sciences
Mr. Mirza Md. Tanjim Shorif Mugdho (TSM)
Lecturer
Department of Computer Science and Engineering
Mr. Mirza Md. Tausif Shorif Snighdho (MIT)
Lecturer
Department of Computer Science and Engineering
Ms. Mahfuza Haque Mahi
Adjunct Faculty Member
Department of Mathematics and Natural Sciences
Mr. Rafeed Rahman Turjya (RRT)
Lecturer
Department of Mathematics and Natural Sciences
Ms. Lubaba Ferdous Alim (LFA)
Vice Chancellor's Fellow
Department of Mathematics and Natural Sciences
Mr. Shehran Syed (SYED)
Vice Chancellor's Fellow
Department of Mathematics and Natural Sciences
Course Coordinator
Shehran Syed (SYED)
Vice Chancellor’s Fellow
Department of Mathematics and Natural Sciences
School of Data and Sciences
Email: [email protected]
Course Curriculum
Frequency distribution; mean, median, mode and other measures of central tendency; standard deviation and other measures of dispersion; measure of skewness; and box-whisker plot; correlation and regression analysis; elementary probability theory; conditional probability and Bayes’ Theorem; combinatorial probabilities; random variables and joint probability distributions; discrete probability distributions: geometric, binomial and Poisson distribution; continuous probability distributions: normal and exponential distributions; statistical hypothesis testing: Z-Test and T-Test.
Course Learning Outcomes (CLOs):
On successful completion of this course, students should be able to:- CLO1: Distinguish between different types of data and describe data using tables and graphs.
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CLO2:
Summarize and analyse data using different summary measures.
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CLO3:
Calculate and interpret results from correlation and regression analysis.
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CLO4:
Demonstrate systematic understanding of the basic concepts of probability, counting principles, and random variables.
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CLO5:
Compute probabilities and make inferences using discrete probability distributions and continuous probability distributions.
- CLO6: Understand and apply the concepts of statistical hypothesis testing to draw conclusions from real-life scenarios.
Course Delivery and Performance Evaluation
- There will be two lectures delivered per week, along with 3 hours of scheduled consultation.
- Students will be evaluated based on their performance on post-lecture assessments, assignments, quizzes, a midterm exam and a final exam.