Descriptive Statistics

1. Descriptive Statistics • Measure of central tendency • Gives a typical value for the data set • Tells you where the middle of the data set is • Measure of dispersion • Indicates how the data are spread out • Tells you what the rest of the data are doing www.psychlotron.org.uk

2. Descriptive Statistics • The aim of descriptive statistics is to give an accurate summary of the data • The wrong choice of statistic gives a distorted picture of the data • This can lead to the wrong conclusions being drawn from the data • Each measure of CT and D has its advantages and disadvantages www.psychlotron.org.uk

3. Measures of Central Tendency • The mean • Adv: it uses all the values in the set, so is most sensitive to variations in the data • Dis: it can be artificially raised or lowered by an extreme value, or by skewed data • Use it when the data are normally distributed, unskewed and there are no outliers www.psychlotron.org.uk

4. Measures of Central Tendency • The median • Adv: it is based on the order of the data, not their actual values, so not distorted by extreme values • Dis: however, this makes it less sensitive to variations in the data • Use it when you can’t use the mean because of skew, outliers etc. www.psychlotron.org.uk

5. Measures of Central Tendency • The mode • Adv: it’s the only measure suitable for summarising category/frequency data • Dis: for many data sets there is no modal value, or their may be several • Use when dealing with frequency data, and/or where there is a clear modal value in the set www.psychlotron.org.uk