Graphical Representation of Data

Flashcards based on lecture notes about graphical representation of data.

Raw Data Tables

Show scores prior to analysis. It is hard to identify patterns in the data. Raw data cannot tell us much.

Frequency Tables

More useful than a raw data table. Can organize the values into groups when there are a large number of them. Patterns in the data are clearer.

Summary Tables

Include measures of central tendency (mean, median, mode) and measures of dispersion (range, standard deviation). Provide a clear summary of data.

Graphs

Summarize quantitative data. Act as a visual aid allowing us to see patterns in a data set. To communicate information effectively, a graph must be clear and simple and have a title and each axis labelled.

Bar Chart

Used to represent ‘discrete data’ where the data is in categories, which are placed on the x-axis. The mean or frequency is on the y-axis. Columns do not touch and have equal width and spacing.

Histogram

Used to represent data on a ‘continuous’ scale. Columns touch because each one forms a single score (interval) on a related scale. Scores (intervals) are placed on the x-axis. The height of the column shows the frequency of values on the y-axis.

Frequency Polygon

Can be used as an alternative to the histogram. Lines show where mid-points of each column on a histogram would reach. Particularly useful for comparing two or more conditions simultaneously.

Scattergram

Used for measuring the relationship between two variables. Data from one variable is presented on the x-axis, while the other is presented on the y-axis. The pattern of plotted points reveals different types of correlation (positive, negative, or no relationship).