- Introduction to Probability
- Basic Terminologies
- Types of Events and Probability Definition
- Approaches to Probability
- Generating Sample Space
What you'll learn
- What is probability and why to learn it. Application of probability
- Basic Terminologies
- Probabilistic or Random Experiment
- Sample Space
- Deterministic Experiments
- Types of Events
- Trial
- Generating Sample Space
- Algebra of Events
- Classical Empirical Subjective Axiomatic
- Mathematics
Description
If you know nothing about probability then, this course is for you. Get a quick detailed explanation of probability.
In this course you will learn followings:
Probability of something happening based on an individual’s own experience or personal judgment
1 Introduction to Probability
2 Basic Terms to Probability
3 Types of Events and Probability Definition
4 Approaches to Probability
5 Generating Sample Space
In this course we have divided all problems related to probability that are asked in exams into three categories:
1. When N(E) and N(S) are determined by counting the elements of EVENT and SAMPLE SPACE.
2. When N(E) and N(S) are calculated by applying permutation and combination.
3. Problems based on P(E) + P(E’) = 1
When an event has a lot of outcomes, then we use this concept.
I will also explain you
History of Probability.
What is probability and why to learn it?
Here I am trying to give a detailed explanation of probability in very short time.
We will also discuss following approaches to find probability:
Classical
Empirical
Subjective
Axiomatic
Algebra of events will also be discussed in which UNION, INTERSECTION, and Complementary and may similar concepts will be discussed.
This course also covers some popular theorems that are very frequently asked and mandatory to learn including Addition theorem of Probability and Multiplication theorem of Probability.
Generating Sample Space: Generation of sample is very important to solve any problem. Since many scenarios are presented in different types of problems. So I will explain you how to we can generate sample space for any type of problem you may face.
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About the instructors
- 4.63 Calificación
- 110 Estudiantes
- 1 Cursos
Yogesh Kakde
Academician with 15 years of experience
I am an Experienced Assistant Professor and Technical Trainer with a demonstrated history of working in the education industry. Skilled in Statistics and probability, Python, R, Machine Learning and Deep Learning. Strong education professional in Computer Science & Engineering. I worked in various universities and colleges as assistant professor and taught various subjects from computer science engineering with data science specialization.
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better for beginner