Calculating Binomial Probabilities (DP IB Analysis & Approaches (AA): HL): Revision Note

Calculating binomial probabilities

Throughout this section we will use the random variable X~B(n, p). For a binomial distribution, the probability of X taking a non-integer or negative value is always zero. Therefore any values of X mentioned in this section will be assumed to be non-negative integers: 0, 1, 2, 3, 4, etc.

How do I calculate P(X = x): the probability of a single value for a binomial distribution?

  • You should have a GDC that can calculate binomial probabilities

  • You want to use the "Binomial Probability Distribution" function

    • This is sometimes shortened to BPD, Binomial PD or Binomial Pdf

  • You will need to enter:

    • The 'x' value - the value of x for which you want to find P(X=x)

    • The 'n' value - the number of trials

    • The 'p' value - the probability of success

  • Some calculators will give you the option of listing the probabilities for multiple values of x at once

  • There is a formula that you can use but you are expected to be able to use the distribution function on your GDC

    • P(X=x)=Cxn×px(1p)nx

      • Cxn=n!x!(nx)!

How do I calculate P(a ≤ X ≤ b): the cumulative probabilities for a binomial distribution? 

  • You should have a GDC that can calculate cumulative binomial probabilities

    • Most calculators will find P(aXb)

    • Some calculators can only find P(Xb)

      • The identities below will help in this case

  • You should use the "Binomial Cumulative Distribution" function

    • This is sometimes shortened to BCD, Binomial CD or Binomial Cdf

  • You will need to enter:

    • The lower value - this is the value a

      • This can be zero in the case P(Xb)

    • The upper value - this is the value b

      • This can be n in the case P(Xa)

    • The 'n' value - the number of trials

    • The 'p' value - the probability of success

How do I find probabilities if my GDC only calculates P(X ≤ x)?

  • To calculate P(Xx) just enter x into the cumulative distribution function

  • To calculate P(X < x) use:

    • P(X<x)=P(Xx1) which works when is a binomial random variable

      • P(X < 5) = P(≤ 4)

  • To calculate P(X > x) use:

    • P(X>x)=1P(Xx) which works for any random variable

      • P(X > 5) = 1 - P(≤ 5)

  • To calculate P(Xx) use:

    • P(Xx)=1P(Xx1) which works when is a binomial random variable

      • P(X ≥ 5) = 1 - P(≤ 4)

  • To calculate P(a Xb) use:

    • P(aXb)=P(Xb)P(Xa1) which works when is a binomial random variable

      • P(5 ≤ ≤ 9) = P(≤ 9) - P(≤ 4)

What if an inequality does not have the equals sign (strict inequality)? 

  • For a binomial distribution (as it is discrete) you could rewrite all strict inequalities (< and >) as weak inequalities (≤ and ≥) by using the identities for a binomial distribution:

    • P(X<x)=P(Xx1) and P(X>x)=P(Xx+1)

    • For example: P(X < 5) = P(X ≤ 4) and P(X > 5) = P(X ≥ 6)

  • It helps to think about the range of integers you want

    • Identify the smallest and biggest integers in the range

  • If your range has no minimum or maximum then use 0 or n

    • P(Xb)=P(0Xb)

    • P(Xa)=P(aXn)

  • P(a<Xb)=P(a+1Xb)

    • P(5 < X ≤ 9) = P(6 ≤ X ≤ 9)

  • P(aX<b)=P(aXb1)

    • P(5 ≤ X < 9) = P(5 ≤ X ≤ 8)

  • P(a<X<b)=P(a+1Xb1)

    • P(5 < X < 9) = P(6 ≤ X ≤ 8)

Examiner Tips and Tricks

If the question is in context then write down the inequality as well as the final answer.

This way you might still gain a mark even if you accidentally type the wrong numbers into your GDC.

Worked Example

The random variable X~B(40, 0.35). Find:

i) P(X=10).

Answer:

4-5-2-ib-ai-aa-sl-binomial-prob-a-we-solution

ii) P(X10).

Answer:

4-5-2-ib-ai-aa-sl-binomial-prob-b-we-solution

iii) P(8<X<15).

Answer:

4-5-2-ib-ai-aa-sl-binomial-prob-c-we-solution

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