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@ -414,9 +414,9 @@ To get probability from a to b (inclusive and exclusive doesn't matter in contin
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\[ E(X + Y) = E(X) + E(Y) \]
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+ Variance
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If
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Variance is
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\[ V(X) = E(X^2) - (E(X))^2 \]
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Then
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Properties of variance are
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\[ V(aX) = a^2 V(X) \]
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\[ V(a) = 0 \]
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@ -436,7 +436,6 @@ The moment generating function is given by
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\[ E(X^n) = (\frac{d^n}{dt^n} M(t))_{t=0} \]
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* Binomial Distribution
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The use of a binomial distribution is to calculate a known probability repeated n number of times, i.e, doing *n* number of trials.
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A binomial distribution deals with discrete random variables.
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@ -733,3 +732,7 @@ Here \sigma is standard deviation.
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+ If $\rho = 0$ then $\theta = \frac{\pi}{2}$
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+ If $\rho = \pm 1$ then $\theta = 0$
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TODO : Maybe an example here
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* Sampling
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Notes not made for this currently, a pdf was provided by teacher as, [[./sampling.pdf][./sampling.pdf]]
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