Probability Distributions
Tamil Nadu Board · Class 12 · Mathematics
Complete topic list for Probability Distributions in Tamil Nadu Board Class 12 Mathematics. Key concepts, sub-topics, and what to focus on for board exams.
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Topics in Probability Distributions
Random Variables
- A random variable X is a function from the sample space S to the real numbers R, i.e., X: S → R
- Random variables are denoted by capital letters (X, Y, Z) and their values by small letters (x, y, z)
- The range set R_x = {X(ω) / ω ∈ S} is the set of all possible values of X
Discrete Random Variables and Probability Mass Function (PMF)
- A discrete random variable X has a countable (finite or countably infinite) range set
- The Probability Mass Function (PMF) f(x) gives the probability that X takes value x: f(xₖ) = P(X = xₖ)
- Two conditions for a valid PMF: (i) f(xₖ) ≥ 0 for all k, and (ii) Σf(xₖ) = 1
Cumulative Distribution Function (CDF)
- CDF F(x) = P(X ≤ x) gives the probability that X takes a value less than or equal to x
- CDF is defined for all real numbers x ∈ R, even though PMF is only defined at discrete points
- CDF is a step function for discrete random variables — it jumps at each value xₖ
Continuous Random Variables and Probability Density Function (PDF)
- A continuous random variable X takes values in an interval — uncountably many values
- For continuous X: P(X = a) = 0 for every single value a — probability at a point is ZERO
- The Probability Density Function (PDF) f(x) satisfies: (i) f(x) ≥ 0 and (ii) ∫_{-∞}^{∞} f(x)dx = 1
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