21-09-2016, 12:58 PM
1455563860-Quantitativedataanalysis.ppt (Size: 308.5 KB / Downloads: 9)
Common myths
Complex analysis and big words impress people.
Most people appreciate practical and understandable analyses.
Analysis comes at the end after all the data are collected.
We think about analysis upfront so that we HAVE the data we WANT to analyze.
Quantitative analysis is the most accurate type of data analysis.
Some think numbers are more accurate than words but it is the quality of the analysis process that matters
Data have their own meaning.
Data must be interpreted. Numbers do not speak for themselves.
Stating limitations to the analysis weakens the evaluation.
All analyses have weaknesses; it is more honest and responsible to acknowledge them.
Computer analysis is always easier and better.
It depends upon the size of the data set and personal competencies. For small sets of information, hand tabulation may be more efficient.
Quantitative data analysis is making sense of the numbers to permit meaningful interpretation
It involves:
organizing the data
doing the calculations
interpreting the information
lessons learned
explaining limitations
Organizing the data
Organize all forms/questionnaires in one place
Check for completeness and accuracy
Remove those that are incomplete or do not make sense; keep a record of your decisions
Assign a unique identifier to each form/questionnaire
Enter your data
By hand
By computer
Excel (spreadsheet)
Microsoft Access (database mngt)
Quantitative analysis: SPSS (statistical software)