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Probability is a branch of Mathematics that
deals with calculating the likelihood of a given
event's occurrence, which is expressed as a
number between 1 and 0.
If you draw a card from a standard deck of
cards , what is the probability of not getting a
heart?
If a bag contains 5 white and 7 red marbles,
what is probability of getting a red marble ?
n = total number of vertices
I = Independent Set =
S = {v1 , v2 , v3 , …........vn }
Repeat the following till S is not empty :
Let's bound the expected size of I
v= a vertex or node of graph
Iv = an indicator variable which indicates whether or not v belongs to I i.e. Iv = 1 if it does belong or 0
V belongs to I if none of its neighbour appear before it in the permunation. This happens with probability 1/dv.
There must be atleast permutation for which
the size of I is at least equal to its expectation.
Initially, I = { }
Let S = {2 , 6 , 7 , 5 , 4 , 3 }
Removing lowest index vertex 2 and its neighbours :
I = { 2 }
S = { 7 , 5 , 3 }
Removing lowest index vertex 7 and its neighbours :
I = { 2 , 7 }
S = { }
= = 2.66
Assume that IQ scores are normally distributed, with a mean µ of 100 and standard deviation of 15. What is the probability that a randomly selected person has an IQ score greater than 110?
Normal distribution, also known as the Gaussian distribution, is a probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean.
Motto : To collect all the coupons and win
Let T be the time to collect all n coupons, and let ti be the time to collect the i-th coupon after i − 1 coupons have been collected.
Think of T and ti as random variables.
By the linearity of expectations we have :
Here Hn is the n-th harmonic number. Using the asymptotics of the harmonic numbers, we obtain :
where , is the Euler–Mascheroni constant.
Now one can use the Markov inequality to bound the desired probability:
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