The characteristics of a normal distribution
- Distribution in psychology refers to the spread of data around the mean for a specific sample or population
- Researchers in psychology are interested in seeing the extent to which one data set varies from the mean i.e. do most scores cluster around the mean, are they spread symmetrically or are they skewed?
- A normal distribution is symmetrical around the mean, with most scores being close to it, showing a peak in the middle where the mean value is located
- The shape of a normal distribution is known as the ‘bell curve’ as when a line is drawn around the histogram bars as in the below example, it looks like a bell
Normal distribution of data
Interpreting normal distribution
- In a perfect normal distribution the mean, mode and median all appear at the peak of the curve i.e. they have similar values
- Scores to the left of the peak represent people who have scored less than the mean
- Scores to the right of the peak represent people who have scored more than the mean
- Each ‘tail’ (the far left and right ends of the curve) never touch the x-axis as there is no assumption made as to what the most extreme score could be (i.e. there could be people in that population who have not been measured for that particular data set who may have lower or higher scores)
- Normal distributions are most likely for the following measurements:
- Height
- Shoe size
- IQ
Worked example
Here is an example of a question you might be asked on this topic - for AO2.
AO2: You need to apply your knowledge and understanding, usually referring to the ‘stem’ in order to do so (the stem is the example given before the question)
Question: Which of the following sets of data is normally distributed?
Select one answer only. [1]
a) mean = 45 median = 44 mode = 43
b) mean = 48 median = 40 mode = 46
c) mean = 47 median = 47 mode = 47
d) mean = 49 median = 46 mode = 44.
Model answer:
- The correct answer is c) mean = 47 median = 47 mode = 47