Analysing your quantitative data – things to think about
Think carefully about your questionnaire, the questions and the data you have (i.e. the variables you have chosen to measure)….You need to be able to code your data. This means giving it a numerical value to represent the answer given:
Q 1: Are you:
Male 1 as assigned value to be “male”Female 2 as assigned value to be “female”
Is this descriptive, ranked, discrete or continuous data?
Some of the data you have collected are numbers or scores or ratings – theyare “points”. Where you have asked:
Rate on a scale 1 to 10….
You need to record these as actual values (they do not need codinglike #1 above). These are numbers that you can manipulate and calculate averages. You can also look for relationships and correlations.
• Are these descriptive, ranked, discrete orcontinuous data?
Some of your data may capture a position on a scale e.g. where you have asked people to “rank” things or where you have used a Likert scale, or used a semantic differential, youwill have collected these types of data.
Remember that the number (value) here is a code for the position in the scale. You cannot treat this in the same way as the data in #2 above. Inyour analysis you will need to count the frequency of each value – that is how many respondents marked a 5, how many a 4, how many a 3 etc (or how many -3, -2 ….. +2, +3)
• Are thesedescriptive, ranked, discrete or continuous data?
So you results will probably be best displayed as a bar chart:
Some things to think about
1. Review your datacollection tool (e.g. questionnaire) and make sure you understand which type of data you have collected. Make a note of this on a copy of the questionnaire. You need this to remind you of what you should and...
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