About Course
Introduction to probability and Statistics
In today’s society, statistical thinking and technique are essential. Every discipline, including physical sciences, engineering and technology, economics, and social sciences, can benefit from it. Statistical methods are increasingly used in advanced research in electronics, electrical, computer science, industrial engineering, biology, genetics, and information science.
It is critical for pupils to become familiar with the subject of probability and statistics as early as possible. The purpose of this course is to introduce the subject to undergraduate and postgraduate science and engineering students.
probability and Statistics Course Outline
Week 01:Sets, Classes, and Collections | Sequence of Sets | Ring, Field (Algebra) | Sigma-Ring, Sigma-Field
Definitions of Probability | Monotone Class | Random Experiment
Conditional Probability | Event Independence | Probability Problems | Random Variables |
Week 02:A Random Variable’s Probability Distribution.
Week 03:A Random Variable’s Probability Distribution-II.
Week 04:Special Continuous Distributions | Poisson Process
Normal Distribution | Normal Distribution Problems | Random Variable Function
Week 05: Joint Distributions | Independence, Product Moments | Correlation and Linearity Property
Week 06 Bivariate Normal Distribution | Examples
Week 07:Basic Concepts | Chi-Square Distribution | Additive Properties of Distributions | Transformation of Random Variables | Distribution of Order Statistics | Basic Concepts|Chi-Square Distribution
Week 08:Chi-Square Distribution | t-Distribution | F-distribution | Descriptive Statistics
Week 09:Introduction to Estimation | Unbiased and Consistent Estimators | LSE, MME | MME, MLE Examples
Week 10: UMVUE, Sufficiency, Completeness | Rao-Blackwell Theorem and its Applications
Course Content
Lecture 01
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