What is a continuous random variable?
- A continuous random variable (often abbreviated to CRV) is a random variable that can take?any value?within a range of infinite values
- Continuous random variables?usually measure?something
- For example, height, weight, time, etc
What is a continuous probability distribution?
What is a normal distribution?
- A normal distribution is a?continuous probability distribution
-
μ?is the?mean
- σ2?is the?variance
- σ?is the?standard deviation
- If the?mean?changes then the graph is?translated horizontally
- If the?variance?changes then the graph is?stretched horizontally
- A?small variance?leads to a?tall?curve with a?narrow?centre
- A?large variance?leads to a?short?curve with a?wide?centre
What are the important properties of a normal distribution?
- The?mean?is?μ
- The?variance?is?σ2
- If you need the?standard deviation?remember to square root this
- The normal distribution is symmetrical about
- Mean = Median = Mode =?μ
- There are the results:
- Approximately?two-thirds (68%)?of the data lies within?one standard deviation?of the mean (μ?±?σ)
- Approximately?95%?of the data lies within?two standard deviations?of the mean?(μ?±2σ)
- Nearly?all of the data (99.7%)?lies within?three standard deviations?of the mean?(μ?±3σ)
Modelling with Normal Distribution
What can be modelled using a normal distribution?
- A lot of real-life continuous variables can be modelled by a normal distribution provided that the population is large enough and that the variable is?symmetrical?with?one mode
- This fact allows us to model variables that are not defined for all real values such as height and weight
What can not be modelled using a normal distribution?
- Variables which have?more than one mode?or?no mode
- For example: the number given by a random number generator
- Variables which are?not symmetrical
- For example: how long a human lives for
Exam Tip
- An exam question might involve different types of distributions so make it clear which distribution is being used for each variable
Worked Example

b)? ? ? State two assumptions that have been made in order to use this model.