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Exercise 11.6 · Q6

Q.Let XX represent the difference between the number of heads and the number of tails obtained when a coin is tossed nn times. Then the possible values of XX are

(1) i+2n, i=0,1,2,…,ni+2n,\ i=0,1,2,\dots,n
(2) 2i−n, i=0,1,2,…,n2i-n,\ i=0,1,2,\dots,n
(3) n−i, i=0,1,2,…,nn-i,\ i=0,1,2,\dots,n
(4) 2i+2n, i=0,1,2,…,n2i+2n,\ i=0,1,2,\dots,n.
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Concept understanding — Random Variable — Discrete and Continuous

A random variable XX is a function defined on a sample space SS into the real numbers R\mathbb R, such that the inverse image of every point, subset or interval of R\mathbb R is an event in SS (Definition 11.1). It turns the outcomes of a random experiment — which need not themselves be numbers, e.g. a coin's head/tail — into numbers we can compute with. Capital letters X,Y,ZX,Y,Z denote the random variable itself; small letters x,y,zx,y,z denote its possible values. If xx is a possible value, its inverse image X−1(x)={ω∈S:X(ω)=x}X^{-1}(x)=\{\omega\in S:X(\omega)=x\} is always an event of SS, so it has a probability — this is what makes "P(X=x)P(X=x)" meaningful.

Two flavours are studied:

  • Discrete random variable (Definition 11.2): its range is countable — finite, or a sequence x1,x2,x3,…x_1,x_2,x_3,\dots — with every value carrying positive probability and the whole range's probabilities summing to 11. Used for counting a quantity: number of heads, number of defectives, a sum of dice faces, a winning amount taking finitely many values. A discrete random variable can even live on a continuous sample space (e.g. a step function of ω∈[0,20]\omega\in[0,20] taking only two values is still discrete, because its range, not its domain, is what is tested for countability). …

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