data is either

1. Qualitiative = Categorical (Ordinal or Nominal)

-Ordinal like likert score e.g, strongly agree, agree, neutral, disagree and strongly disagree because it has an order

-Nominal like male and female , yes or no and nationality

2. Quantitative (Scale either discrete or continuous)

- Discrete like number of children where you can not have 2.5 either 1, 2, 3 etc

- Continuous like weight you can have 50 kg or 70.4 kg etc

to do analysis:

1: if you are comparing two or more type of data where all categorical you use chi square test.

2: if all continuous you use multivariate analysis

3: if comparing continous vs two categories you use t-test

4: if comparing continous vs more than two categories you use anova

This website may help you

http://www.ats.ucla.edu/stat/mult_pkg/whatstat/

NVIVo can be used for this analysis, it is specifically designed to analyse qualitative data.

In addition, you can still transform all the text format into a quantitative data and analyze it via spss hence it is only the descriptive statistics you need to describe and summarize your data

I have a publication generated from qualitative data, you can borrow a leave from it

data is either

1. Qualitiative = Categorical (Ordinal or Nominal)

-Ordinal like likert score e.g, strongly agree, agree, neutral, disagree and strongly disagree because it has an order

-Nominal like male and female , yes or no and nationality

2. Quantitative (Scale either discrete or continuous)

- Discrete like number of children where you can not have 2.5 either 1, 2, 3 etc

- Continuous like weight you can have 50 kg or 70.4 kg etc

to do analysis:

1: if you are comparing two or more type of data where all categorical you use chi square test.

2: if all continuous you use multivariate analysis

3: if comparing continous vs two categories you use t-test

4: if comparing continous vs more than two categories you use anova

This website may help you

http://www.ats.ucla.edu/stat/mult_pkg/whatstat/

I agree with Ahmad. If your data are qualitative, you use chi square test. I attach a simple educational article on chi square statistics.

You can also score your data and use quantitative statistics. The choice of the test then depends on the sample size, type of the distribution, number of groups, variance etc...

There is a good paper describing the simple rules on how to choose the right statistical test:

Marusteri M, Bacarea V. Comparing groups for statistical differences: how to choose the right statistical test? Biochemia Medica 2010;20(1):15-32. http://dx.doi.org/10.11613/BM.2010.004

Hope this helps.

Thank you all.

Nvivo

In addition to the statistical methods some colleagues recommended you above, I think that a method visual representation of data can enables you to answer qualitatively your analytical tasks. A computer graphics software converts your data table to graphs with a method of visualization suitable for data variables and your problems. Based on the graphs and your available knowledge of specialty, you can answer qualitatively analytical tasks.

Principal component can help a lot. You can compute the principal component of funcions of the quantatties increasing the strength of the computations

Ana-Maria, that for sharing. I will be working on qualitative data and I find your information very helpful since I am new to this area.

Thanks

Charles

I perfectly agree to Sempeho's explanation. One must learn how to use the software and even be able to interpret the final result.