# Representing Data using tables graphs and averages

Edited by Jamie (ScienceAid Editor), Taylor (ScienceAid Editor), SmartyPants

## Tables

For Psychologists, tables are a very important tool. The title should be informative with the units stated clearly. The column titles should allow you to know exactly what the results show. Below is a table with the results from an experiment where students who had eaten breakfast, and students did not eat breakfast, did a maths test.

## Graphs

Graphs are a good way of visually representing your findings in a study. The first one is a histogram. They are different to the bar charts because their scale is continuous (1,2,3,4,5 rather than red, blue and green), so the bars are put next to each other. In a 'proper' histogram, there is frequency density, but for the purposes of Psychology, we will only look at frequency which means the 'number of'.

Another type of graph that you may encounter is a scatter graph. This is done by plotting one thing against another, and will show a correlation. As well as a visual representation, there are a number of methods that we can use to calculate correlation numerically. A correlation of +1 would be perfect positive correlation and a correlation of -1 is perfect negative. Having a correlation of 0, would determine there is no relationship at all. The diagram below outlines this.

## Averages and Distribution

Another term for average is measures of central tendency. So an average gives an indication as to the most typical result; there are three main types"

1. 1
Mode - the most frequent piece of data - i.e
.
- the one that appears the most.
2. 2
Median.
3. 3
Mean.

The distribution of some data can also be called its spread. The easiest method is called the range and you simply subtract the smallest value from the largest. However, this is not entirely accurate. This is why statisticians have devised a measure called standard deviation. Put simply this measure tells you how much the data deviates (is smaller or larger than) the mean; on average. It is relative to the size of the mean.

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## Article Info

Categories : Approaches

Recent edits by: Taylor (ScienceAid Editor), Jamie (ScienceAid Editor)