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Introduction to Data Analytics
Lecture: Random Variables and Probability distributions – 1
NPTEL MOOC
By
Prof. Nandan Sudarsanam, DoMS, IIT-M and
Prof. B. Ravindran, CS&E, IIT-M
• Random Variable: A variable whose value is subject to variations due
to randomness.
• The mathematical function describing this randomness (the
probabilities for the set of possible values a random variable can take)
is called a probability distribution.
• Continuous and Discrete probability density functions
• Discrete
Random Variables
Event No Event
x
1-x
1/6
Probability
Probability
Heads Tails
14/30 16/30
Probability
1 2 3 4 5 6
• Continuous Distributions
• Probability of certain height
• Total Probability of all outcomes
Random variables
Probability
height
• Probability Density functions (PDFs) and Cumulative Density
Functions (CDF)
• Going from PDF to CDF and vice versa
Random Variables
Probability
height
Probability
height
1.0
PDF CDF

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Probability

  • 1. Introduction to Data Analytics Lecture: Random Variables and Probability distributions – 1 NPTEL MOOC By Prof. Nandan Sudarsanam, DoMS, IIT-M and Prof. B. Ravindran, CS&E, IIT-M
  • 2. • Random Variable: A variable whose value is subject to variations due to randomness. • The mathematical function describing this randomness (the probabilities for the set of possible values a random variable can take) is called a probability distribution. • Continuous and Discrete probability density functions • Discrete Random Variables Event No Event x 1-x 1/6 Probability Probability Heads Tails 14/30 16/30 Probability 1 2 3 4 5 6
  • 3. • Continuous Distributions • Probability of certain height • Total Probability of all outcomes Random variables Probability height
  • 4. • Probability Density functions (PDFs) and Cumulative Density Functions (CDF) • Going from PDF to CDF and vice versa Random Variables Probability height Probability height 1.0 PDF CDF