Mean
- The mean calculates the average score of a data set
- The mean indicates what a researcher would expect to find (as the average score) if they were to replicate the procedure of a given study
- The mean is calculated using the total score of all the values in the data set divided by the number of values in that set, e.g.
- To calculate the mean of 4, 6, 7, 9 the researcher would add up the values and then divide this total by the number of values as follows:
- 4 + 6 + 7 + 9 = 26
- 26 ÷ 4 = 6.5
- mean = 6.5
- 4 + 6 + 7 + 9 = 26
- To calculate the mean of 4, 6, 7, 9 the researcher would add up the values and then divide this total by the number of values as follows:
- Advantages of using the mean
- It is the most sensitive measure of central tendency as it takes all scores in the data set into account
- It is more likely than other measures of central tendency to provide a representative score i.e. a reliable result
- Disadvantages of using the mean
- It is sensitive to extreme scores (outliers) so it can only be used when the scores are reasonably close
- The mean score may not be represented in the data set itself: in the example above, the mean is 6.5 which does not appear in the original data set