Data analysis

By Tutorial 2 you will be able to download the collated data file containing several hundred cases.

Basically, the approach to analysis should follow two stages:

Measurement validation

Conduct and report on:

  1. qualitative analysis of at least one of the open-ended motivation or satisfaction questions as a way of examining the validity of the empirical measures.
  2. exploratory factor analysis, reliability analyses, and the creation of composite scores for motivation and satisfaction.

These analyses constitute intermediate techniques for creating reliable and valid data for the substantive analyses; they aren't the focus of the research question.

Hypothesis testing

Once you have derived suitable measures of motivations and satisfaction, address the research question by testing your hypotheses (which you will have stated towards the end of the introduction).  To test the hypotheses, report on the results of at least one each of:

  1. multiple regression analysis, and
  2. advanced ANOVA

You can also report any additional analyses that you deem appropriate, however it will be possible to gain maximum marks by using just regression/ANOVA for hypothesis testing, along with relevant descriptive statistics.  Note that you do not need to analyse all the data from the survey -- only analyse and discuss data relevant to your hypotheses.

See also