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Edexcel A Level Maths: Statistics

Revision Notes

Home / A Level / Maths: Statistics / Edexcel / Revision Notes / 4. Statistical Distributions / 4.3 Normal Distribution (A Level only) / 4.3.2 Normal Distribution - Calculations


4.3.2 Normal Distribution - Calculations


Throughout this section we will use the random variable X tilde straight N left parenthesis mu comma sigma squared right parenthesis. For a normal distribution, X can take any real number. Therefore any values mentioned in this section will be assumed to be real numbers.

Calculating Normal Probabilities

How do I find probabilities using a normal distribution?

  • The area under a normal curve between the points begin mathsize 16px style x equals a end style and begin mathsize 16px style x equals b end style is equal to the probability begin mathsize 16px style P left parenthesis a less than X less than b right parenthesis end style
    • Remember for a normal distribution so you do not need to worry about whether the inequality is strict (< or >) or weak (≤ or ≥)
  • The equation of a normal distribution curve is complicated so the area must be calculated numerically
  • You will be expected to use distribution functions on your calculator to find the probabilities when working with a normal distribution

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

  • The probability of a single value is always zero for a normal distribution
    • You can picture this as the area of a single line is zero
  • P(X = x ) = 0
  • Your calculator is likely to have a "Normal Probability Density" function
    • This is sometimes shortened to NPD, Normal PD or Normal Pdf
    • IGNORE THIS FUNCTION for this course!
    • This calculates the probability density function at a point NOT the probability

How do I calculate, P(a < X < b)  the probability of a range of values for a normal distribution?

  • You need a calculator that can calculate cumulative normal probabilities
  • You want to use the "Normal Cumulative Distribution" function
    • This is sometimes shortened to NCD, Normal CD or Normal Cdf
  • You will need to enter:
    • The 'lower bound' - this is the value a
    • The 'upper bound' - this is the value b
    • The 'µ' value - this is the mean
    • The 'begin mathsize 16px style sigma end style' value - this is the standard deviation
  • Check the order carefully as some calculators ask for standard deviation before mean
    • Remember it is the standard deviation (so if you have the variance then square root it)
  • Always sketch a quick diagram to visualise which area you are looking for

How do I calculate, P(X>a) or P(X<b) for a normal distribution?

  • You will still use the "Normal Cumulative Distribution" function
  • P(X > a) can be estimated using an upper bound that is sufficiently bigger than the mean
    • Using a value that is more than 4 standard deviations bigger than the mean is quite accurate
    • Or an easier option is just to input lots of 9's for the upper bound (99999999.. or 1099)
  • Similarly P(X < b) can be estimated using a lower bound that is sufficiently smaller than the mean
    • Using a value that is more than 4 standard deviations smaller than the mean is quite accurate
    • Or an easier option is just to input lots of 9's for the lower bound with a negative sign (-99999999... or -1099)
  • This works because the probability that X is more than 3 standard deviations bigger than the mean is less than 0.0015
    • This is the same for being 3 standard deviations less than the mean
    • This reduces to less than 0.000032 when using 4 standard deviations

Are there any useful identities?

  • straight P left parenthesis X less than mu right parenthesis space equals space straight P left parenthesis X greater than mu right parenthesis equals 0.5
  • As P left parenthesis X equals a right parenthesis equals 0 you can use:
    • straight P left parenthesis X less than a right parenthesis plus straight P left parenthesis X greater than a right parenthesis space equals 1
    • straight P left parenthesis X greater than a right parenthesis equals 1 minus straight P left parenthesis X less than a right parenthesis space
    • straight P left parenthesis a less than X less than b right parenthesis space equals P left parenthesis X less than b right parenthesis minus P left parenthesis X less than a right parenthesis
  • These are useful when:
    • The mean and/or standard deviation are unknown
    • You only have a diagram
    • You are working with the inverse distribution

Worked Example

The random variable Y tilde straight N left parenthesis 20 comma 5 squared right parenthesis. Calculate:

(a)
straight P left parenthesis Y space equals space 20 right parenthesis,
(b)
straight P left parenthesis 18 less or equal than Y less than 27 right parenthesis,
(c)
straight P left parenthesis Y greater than 29 right parenthesis.
(a)
straight P left parenthesis Y space equals space 20 right parenthesis

4-3-2-calculating-normal-probabilities-we-solution-part-1

(b)
straight P left parenthesis 18 less or equal than Y less than 27 right parenthesis

4-3-2-calculating-normal-probabilities-we-solution-part-2

(c)
straight P left parenthesis Y greater than 29 right parenthesis
4-3-2-calculating-normal-probabilities-we-solution-part-3

Inverse Normal Distribution

Given the value of P(X < a) how do I find the value of a ?

  • Your calculator will have a function called "Inverse Normal Distribution"
    • Some calculators call this InvN
  • Given that P(X < a) = p  you will need to enter:
    • The 'area' - this is the value p
      • Some calculators might ask for the 'tail' - this is the left tail as you know the area to the left of a
    • The 'μ' value - this is the mean
    • The 'σ' value - this is the standard deviation
  • Always check your answer makes sense
    • If P(X < a)  is less than 0.5 then a should be smaller than the mean
    • If P(X < a) is more than 0.5 then a should be bigger than the mean
    • A sketch will help you see this

Given the value of P(X > a) how do I find the value of a  ?

  • Given P(X > a) = p
  • Use P(X < a) = 1 - P(X > a)  to rewrite this as P(X < a) = 1 - p
  • Then use the method for (X < a) to find a
  • If your calculator does have the tail option (left, right or centre) then you can use the "Inverse Normal Distribution" function straightaway by:
    • Selecting 'right' for the tail
    • Entering the area as 'p'

Worked Example

The random variable  W space tilde straight N left parenthesis 50 comma space 36 right parenthesis.

Find the value of w such that  straight P left parenthesis W space greater than space w right parenthesis equals 0.175 .

4-3-2-inverse-normal-distribution-we-solution

Exam Tip

Always ask yourself two questions:

  • Have you entered the mean and the standard deviation in the correct order?
  • Have entered the standard deviation correctly and not the variance?


  • 1. Statistical Sampling
    • 1.1 Sampling & Data Collection
      • 1.1.1 Sampling & Data Collection
    • 2. Data Presentation & Interpretation
      • 2.1 Statistical Measures
        • 2.1.1 Basic Statistical Measures
          • 2.1.2 Frequency Tables
            • 2.1.3 Standard Deviation & Variance
              • 2.1.4 Coding
              • 2.2 Data Presentation
                • 2.2.1 Data Presentation
                  • 2.2.2 Box Plots & Cumulative Frequency
                    • 2.2.3 Histograms
                    • 2.3 Working with Data
                      • 2.3.1 Outliers & Cleaning Data
                        • 2.3.2 Intrepreting Data
                        • 2.4 Correlation & Regression
                          • 2.4.1 Correlation & Regression
                          • 2.5 Further Correlation & Regression (A Level only)
                            • 2.5.1 PMCC & Non-linear Regression
                              • 2.5.2 Hypothesis Testing for Correlation
                            • 3. Probability
                              • 3.1 Basic Probability
                                • 3.1.1 Calculating Probabilities & Events
                                  • 3.1.2 Venn Diagrams
                                    • 3.1.3 Tree Diagrams
                                    • 3.2 Further Probability (A Level only)
                                      • 3.2.1 Set Notation & Conditional Probability
                                        • 3.2.2 Further Venn Diagrams
                                          • 3.2.3 Further Tree Diagrams
                                            • 3.2.4 Probability Formulae
                                          • 4. Statistical Distributions
                                            • 4.1 Probability Distributions
                                              • 4.1.1 Discrete Probability Distributions
                                              • 4.2 Binomial Distribution
                                                • 4.2.1 The Binomial Distribution
                                                  • 4.2.2 Calculating Binomial Probabilities
                                                  • 4.3 Normal Distribution (A Level only)
                                                    • 4.3.1 The Normal Distribution
                                                      • 4.3.2 Normal Distribution - Calculations
                                                        • 4.3.3 Standard Normal Distribution
                                                        • 4.4 Choosing Distributions (A Level only)
                                                          • 4.4.1 Modelling with Distributions
                                                            • 4.4.2 Normal Approximation of Binomial
                                                          • 5. Hypothesis Testing
                                                            • 5.1 Hypothesis Testing
                                                              • 5.1.1 Hypothesis Testing
                                                              • 5.2 Hypothesis Testing (Binomial Distribution)
                                                                • 5.2.1 Binomial Hypothesis Testing
                                                                • 5.3 Hypothesis Testing (Normal Distribution) (A Level only)
                                                                  • 5.3.1 Sample Mean Distribution
                                                                    • 5.3.2 Normal Hypothesis Testing
                                                                  • 6. Large Data Set
                                                                    • 6.1 Large Data Set
                                                                      • 6.1 Large Data Set


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                                                                    Author: Daniel

                                                                    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.


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