Modelling with Distributions (Edexcel A Level Maths): Revision Note

Dan Finlay

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Modelling with Distributions

When should I use a binomial distribution?

  • A random variable that follows a binomial distribution is a discrete random variable

  • A binomial distribution is used when the random variable counts something

    • The number of successful trials

    • The number of members of a sample that satisfy a criterion (satisfying the criteria can be seen as a successful trial)

  • There are four conditions that X must fulfil to follow a binomial distribution

    • There is a fixed finite number of trials (n)

    • The trials are independent

    • There are exactly two outcomes of each trial (success or failure)

    • The probability of success (p is constant

When should I use a normal distribution?

  • A random variable that follows a normal distribution is a continuous random variable

  • A normal distribution is used when the random variable measures something and the distribution is:

    • Symmetrical

    • Bell-shaped

  • A normal distribution can be used to model real-life data provided the histogram for this data is roughly symmetrical and bell-shaped

    • If the variable is normally distributed then as more data is collected the outline of the histogram should get smoother and resemble a normal distribution curve

4-4-1-modelling-with-distributions-diagram-1

Can the binomial distribution and the normal distribution be used in the same question?

  • Some questions might require you to first use the normal distribution to find the probability of success and then use the binomial distribution

  • These questions normally involve some sort of sampling

  • The key is to make sure you are very clear about what each parameter/variable represents

Worked Example

In a population of cows, the masses of the cows can be modelled using a normal distribution with mean 550 kg and standard deviation 80 kg. A farmer classifies cows as beefy if they weigh more than 700 kg. The farmer takes a random sample of 10 cows and weighs them.

Find the probability that at most one cow is beefy.

4-4-1-modelling-with-distributions-we-solution

Examiner Tips and Tricks

  • Always state what your variables and parameters represent.  Make sure you know the conditions for when each distribution is (or is not) a suitable model.

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Dan Finlay

Author: Dan Finlay

Expertise: Maths Lead

Dan graduated from the University of Oxford with a First class degree in mathematics. As well as teaching maths for over 8 years, Dan has marked a range of exams for Edexcel, tutored students and taught A Level Accounting. Dan has a keen interest in statistics and probability and their real-life applications.