Analysing a single scale variable
Part 4: Reporting
If we combine all the reporting bits from the example, the full report for this variable, might have looked something like:
The HRM department was interested to know about the age distribution of the customers. They believe that the average age of a customer is 50 years old. To investigate this Figure 1 shows the results of the age from the survey.
As can be seen Figure 1 there are few customers younger than 25, but the peak is at 25-35, after that there is a steady drop of ages The mean age of customers was 48.19 years, 95% CI [47.4, 49.0], but quite some variation between the customers (SD = 17.69).
The claim that the average age is 50 years old can be rejected, t(1968) = -4.53, p < .001, with a weak effect size (d = .10).
Although the average age is therefor most likely not 50 years old, the difference with the sample average was not very high.
Note the final paragraph explains the some-what technical results into more understandable English, something many readers would often appreciate.
Single scale variable