Presenting Quantitative Results
In general, quantitative studies generate less data than qualitative studies. When datasets are small, it may be possible to present your entire results without summary in some cases.
However, when distributions are involved, simple descriptive statistics can actually add value to a presentation. Thus,
"30 values with a mean of 15, and a maximum of 19 and a minimum of 12" may communicate better than
"17 13 16 14 12 18 15 16 14 13 19 17 14 16 18 12 14 12 13 18 17 14 15 16 14 15 17 12 13 15"
Tables can be a good way of structuring the presentation of data. They can draw attention to key values when they might get lost in a prose description.
Graphs are good at showing trends or relative values, but can lose detail of actual values. For example, they can illustrate the responses to a Likert scale question and show the relative proportions of responses.
However, there are some common pitfalls. Students often seem to feel obliged to "sex up" their data by using unnecessarily complex statistics or software tools. SPSS is not an appropriate tool to calculate a simple mean. If you are going to use it to more fully describe a distribution, in terms of, for example, a mean and a standard deviation, then you need to understand the difference between parametric and non-parametric statistics and be able to show that your data conforms to a normal distribution.
Charts can cause trouble, too. Again it's good advice to keep it simple. 3-D charts look nice but actually obscure the results. There is evidence to suggest that people find pie charts difficult to read.
And, finally, be careful of percentages. It's always worth quoting the absolute value as well. 5% of 20 quoted as 4 (5%) or 5% (n=4) is often a very different result from 5% of 20000. Percentages can be tricky anyway, as you need to make clear to the reader what it represents. For example, the statement, "we found that putting up a poster in a bar reduced drink driving by 5%" can be interpreted as 5% of all drivers would not drink and drive or 5% of those who would have driven home after drinking will no longer do so.