The Normal Distribution

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The Normal Distribution

The normal distribution is a bell shaped curve that is symmetric about the mean. It is defined by its mean μmu and its standard deviation σsigma. If XX is normally distributed, we write XN(μ,σ2)Xsim N(mu,sigma^{2}).

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Facts About the Normal Distribution

Probability is represented by the area under the graph (note this means the total area under the graph is 11).

The normal distribution is symmetric about the mean μmu, which means:

P(Xμ)=P(Xμ)=0.5mathbb{P}(Xgeqmu)=mathbb{P}(Xleqmu)=0.5

P(Xμ+a)=P(Xμa) for all amathbb{P}(Xgeqmu+a)=mathbb{P}(Xleqmu-a)text{ for all }a

The standard deviation determines how flat the graph is – the higher the standard deviation, the lower the graph.

The graph tends to 00 as it travels away from the mean, but it never gets there.

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Using a Calculator for the Normal Distribution

Your calculator might have a built in function for normal distribution probabilities.

This will ask you to put in a mean and standard deviation and an upper and lower bound on XX to produce a probability.

This is fairly straightforward for questions such as P(3X6)mathbb{P}(3leq Xleq 6), but what about questions such as P(X5)mathbb{P}(Xleq 5), where there is no lower bound?

In this case, take the lower bound to be as low as your calculator allows you to input, so that it has as little effect on the result as possible.

Usually, 9999-9999 for a lower bound or 99999999 for an upper bound will suffice.

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The Inverse Normal Function

Sometimes, you might be given a probability pp and asked to find xx such that p=P(X<x)p=mathbb{P}(X<x).

For this, we use the inverse normal function, which should also be on your calculator.

You will input a mean, standard deviation and probability and the calculator gives you xx such that p=P(X<x)p=mathbb{P}(X<x).

Note: For << and leq you can do this directly on your calculator. However, for >> and geq you need to subtract pp from 11 to turn P(X>a)P(X > a) into P(Xa)=1pP(X leq a) = 1-p, then you can use your calculator as normal. 

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Example: The Normal Distribution

In the 20122012 Olympics Men’s 100100 metre sprint final, the average time taken was 1010 seconds. The times were normally distributed with a variance of 0.20.2 seconds. Calculate the probability of a runner having finished the race in 9.589.58 seconds or less.

[2 marks]

XN(10,0.2)Xsim N(10,0.2)

Use your calculator, upper bound 9.589.58 and lower bound 9999-9999

P(X9.58)=0.1738mathbb{P}(Xleq 9.58)=0.1738

The probability of a runner finishing the race in 9.589.58 seconds or less is 0.17380.1738

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The Normal Distribution Example Questions

Question 1: For XN(4,1)Xsim N(4,1), calculate:

a) P(X3.5)mathbb{P}(Xleq 3.5)

b) P(X6)mathbb{P}(Xgeq 6)

c) P(X4.25)mathbb{P}(Xleq 4.25)

[3 marks]

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a) 0.30850.3085

b) 0.02280.0228

c) 0.59870.5987

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Question 2: For XN(75,100)Xsim N(75,100), calculate:

a) P(90X110)mathbb{P}(90leq Xleq 110)

b) P(65X75)mathbb{P}(65leq Xleq 75)

c) P(50X100)mathbb{P}(50leq Xleq 100)

[3 marks]

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a) 0.06660.0666

b) 0.34130.3413

c) 0.98760.9876

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Question 3: For XN(20,25)Xsim N(20,25), find the value of aa such that:

a) P(X>a)=0.1mathbb{P}(X>a)=0.1

b) P(Xa)=0.6mathbb{P}(Xleq a)=0.6

c) P(15Xa)=0.4mathbb{P}(15leq Xleq a)=0.4

[4 marks]

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a) a=26.41a=26.41

b) a=21.27a=21.27

c) a=20.74a=20.74

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Question 4: The weights of punnets of strawberries sold by a greengrocers are 250 g250text{ g} on average with a standard deviation of 9 g9text{ g}. What is the probability that Jenny gets a 280 g280text{ g} punnet or better from the grocers?

[2 marks]

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We model this problem with XN(250,81)Xsim N(250,81).

We want to find P(X280)mathbb{P}(Xgeq 280)

P(X280)=1P(X280)=1P(X280)=10.9996=0.0004begin{aligned}mathbb{P}(Xgeq 280)&=1-mathbb{P}(Xleq 280)[1.2em]&=1-mathbb{P}(Xleq 280)[1.2em]&=1-0.9996[1.2em]&=0.0004end{aligned}

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Additional Resources

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Specification Points Covered

N2 – Understand and use the Normal distribution as a model; find probabilities using the Normal distribution Link to histograms, mean, standard deviation, points of inflection and the binomial distribution