Presentation and display of quantitative data

Specification: Presentation and display of quantitative data: graphs, tables, scattergrams, bar charts, histograms.

Graphical techniques and tables are used to summarise data in a clear and visually accessible way. 

Tables

Perhaps the most straightforward way of presenting data is in tables, which will summarise the key descriptive statistics for a data set, for example, the mean values and standard deviation values for each condition within a psychological investigation. Presenting data in this way will allow the reader to easily compare the most important values, without needing to interpret the data. For example, the following table outlines the mean scores and standard deviation for Godden and Baddeley’s (1975) study.

Scattergram

A scattergram (sometimes called a scattergraph) is a graph that shows the correlation between two sets of data (covariables) by plotting points to represent each pair of scores. It indicates the degree and direction of the correlation between the covariables, one of which is indicated on the Xaxis and the other on the Yaxis.

Bar chart

Bar charts are used to show frequency data for discrete (separate) variables, e.g. used to plot mean scores separately for conditions A and B (and C, D, E…). For example, the following bar chart below demonstrates the results from Loftus and Palmer (1974).

Histogram

A histogram is somewhat similar in appearance to a bar chart, and there is often confusion between the two. The key difference is that a histogram has the bars touching each other, whereas a bar chart has a gap between each. The reason for this is that a histogram is presenting continuous data (e.g. ages 0–9, 10–19, 20–29, etc.). Furthermore, the y axis on a histogram represent frequency whereas on a bar char it represents the value.

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