Presentation & Display of Data

• When writing up the results of their research, psychologists tend to display findings in graphs and tables.
• A table is a simple way to display numerical findings — usually in the form of descriptive statistics such as the mean and standard deviation.
• It is often easier for the reader to find information in a table than from a written text.
• Tables can also be used to summarise qualitative data.

• A chart shows the data in a more visual way. It can be helpful to illustrate smaller and larger differences between conditions.

The bar chart is the most commonly used type of graph in psychology research:

• The bar chart usually shows the IV along the base (x axis).
• The DV is shown up the side (y-axis), with the height of the bars indicating the mean score.
• Each bar represents one condition of the IV.

• Histograms and pie charts are less frequently used.
• A histogram shows a continuous variable along the horizontal (x) axis, such as the age range of different participants, and line graphs have a similar purpose.
• A pie chart should represent fractions of a whole. It is not the right choice for showing the DV in a study, but could be used to describe characteristics of a sample.

• Scattergrams are only used to show correlations, not the results of experiments.

• The normal distribution describes a set of data where scores are very common in the middle of the distribution (close to the mean) and become progressively less common the further they are from the mean.
• IQ is an example of a normally-distributed variable.
• On a line graph, a normal distribution appears as a bell-shaped curve.

• A normal distribution has certain mathematical properties:
  • 50% of scores fall above the mean, and the other 50% below the mean.
  • Approximately 68% of scores fall within one standard deviation above or below the mean.
  • Approximately 95% of scores fall within two standard deviations above or below the mean.
  • Each tail of the graph gets progressively closer to zero, meaning that they become less and less common as they get further from the mean.

• A skewed distribution is similar to the normal distribution’s bell-shaped curve but the bulk of scores fall more to one side of the median score, with a longer ‘tail’ on the other.
• A very difficult test or exam may result in a skewed distribution, with many low scores and only a few high scores.
• Average income is also skewed - most people are at or below the median income, and only a few have very high incomes.