Understanding Descriptive Statistics

Definition of Descriptive Statistics

Descriptive statistics are used to summarise and organise data in a clear and understandable way.
It includes measures of central tendency, variability, and distribution patterns.

Measures of central tendency describe the centre point or typical value of data.
The three main types are: mean (average), median (middle value) and mode (most common value).
The mean is the sum of all scores divided by the number of scores, while the median is the value that separates the highest half of data from the lowest half.
The mode is the most frequently occurring value in a set of data.

Measures of variation define how much the scores in a data set are spread out. They include range, variance, and standard deviation.
The range is the difference between the highest and the lowest score.
The variance measures how far each number in the set is from the mean.
The standard deviation is the square root of the variance, and it indicates the average amount of variation in the data set.

The values collected in research can be organised in a frequency distribution, which shows how frequently each value occurs.
A histogram provides a visual representation of data distribution. It uses bars to show the frequency of data points in different ranges.
A scattergraph shows the relationship between two sets of data. Each point on the graph corresponds to an individual’s scores on two variables.
The normal distribution or ‘bell curve’ is a specific pattern of data distribution where most scores are around the median, with the frequency decreasing as scores get further from the median.

Descriptive statistics provide a straightforward summary of data, making it easier to comprehend complex data sets.
They enable researchers to communicate findings to others in a comprehensible manner.
The use of descriptive statistics should be combined with inferential statistics to best describe and interpret the data.