Question

•Provide one (1) real-life example or application of a binomial distribution. Explain how the example matches the conditions for the binomial distribution.

•Determine the conditions under which you would use a discrete probability distribution rather than a continuous probability distribution. Provide one (1) example to illustrate your reasoning

Answer 1

The following are the conditions for a Binomial Distribution-

• The experiment should have n- identical trails
• The outcomes should be only 2- Success/Failure
• All trails are independent of each other
• The probability of success/failure is same in all trails

Real Life example- Coin toss during a 5 match ODI series between Australia and England

No. of trails=5

Probability of success/Getting a head, if defined= 1/2

Probability of failure/Getting a tail, if defined= 1/2

All trails are independent and there are no possible outcomes other than these two

The following are the conditions for a Discrete Probability Distribution-

• It lists probability of occurence of each value a discrete random variable can take
• The outcomes are limited- 0 or 1, H or T
• You cannot find exactly that the probability is equal to some value in this distribution other than the pre-defined values like in the case of a continuous distribution

Ex: Binary Logic Decoder

Outcomes possible are only 0 and 1

You cannot calculate the probability for outcome = 0.5

Sum of probabilities of outcomes= 0.5+0.5= 1

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