Hey, I used a survey with Likert scale data to identify the requirements to design n ICT intervention for occupational stress management. Now I'm trying to find an appropriate way to analyze my dataset to get an insight on user requirements (prioritize the requirements). If you have any ideas or similar type of studies/methods please share.
Thanks in advance.
Have you gotten an answer yet? if not send me a mail to [email protected] let me see the data and know how to help. happy researching
You can use IBM SPSS to analyze data and that has quite a number of parametric and non-parametric tests. However without looking at your data set its difficult to recommend what tests you should conduct. If your data is normally distributed, you can go for parametric tests and if its not normally distributed you have to go for non-parametric tests.
How big is the dataset? Is it categorized already?(e.g. multiple choice...)
For small datasets of a few thousand lines, usually excel is fine, even with a plugin to visualize.. bigger data generally comes in some csv files, which can be dumped into sql databases.
Often it gives good insights not working with the whole dataset, but to start your analysis with smaller pieces first, and then stepwise narrow.
And of cause one can make sophisticated thinks with statistical software.... to name R as free one, photon has not to high hurdles, others seem to use Wolfram alpha.
But from practical approach often a good editor and a CSV- file as well as string search find, delivers already.
Then you make a result matrix, and start to work.
Have you categorised the data or know what factor or construct each question is measuring? The likert scale measures degree on whatever point scale that people agree or disagree with the statement. For example :
The first part includes 23 statements related to IT performance and the second part has 28 items related to dealing with stress. A total score as well as six subscores including the following are generated with this instrument. Descriptive stats Means, min and max scores and possibly multiple regression can be used to determine relationship of the variables being studied.
The overall prioritization and selection of the right business and IT
change requirements are an important area in the software engineering process as
this is a critical factor that can ultimately impact the success of the business. In
most cases, the overall prioritization of business and IT change requests and the
steps involved in the decision-making process are not transparent enough for all
stakeholders. Therefore it is essential that the business change request management
process is visible and understandable in order to make the right decisions that
are acceptable for all stakeholders. For this reason, the prioritization and selection
process should be built in an effective and efficient way by using quantitative
tools, for example, by following Six Sigma methodology.
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