- 1 Importing the data into the software and creating a summary report
- 2 Summary tables of grid questions
- 3 Creating a crosstab
- 4 Filtering the data
- 5 Creating NETs
- 6 Rebasing tables
- 7 Charts
- 8 Changing metadata
- 9 Computing minimums, medians and maximums
- 10 Recoding numeric data
- 11 Simple predictive model
- 12 Creating market segments
- 13 Reporting and sharing results
- 14 See also
Importing the data into the software and creating a summary report
- Download the example SPSS data file and questionnaire (e.g., to your downloads folder or to your desktop).
- Login to DataCracker (first obtain a trial account if you do not already have one).
- Click on My reports > +Upload data
- Press Upload file.
- Select the file that you saved in the first step and press Open.
- Select Yes, a short report and click Next >.
- Select the bottom-middle option (table with text) and press Create report
The different variables and questions in the study are listed down the left. A table, or chart if selected earlier, is shown on the left of the page. A summary of the data is shown on the right of the page. Hints and tips are shown on the far right of the table.
Summary tables of grid questions
Grid questions are automatically identified when the data is red into DataCracker. Additionally, they can be set within a study by combining related variables (Data Manipulation > Structure > Combine) and by selecting grids from the Structure gallery.
Creating a crosstab
In this example we will create a crosstab of Unaided awareness by age:
- Press , which takes a copy of the current table. We will then modify this copy (this is the basic workflow of Q; tables are created as modifications of existing tables).
- Click on the blue menu/box which currently says Grid and select Unaided awareness.
- Type age into light brownish menu which currently displays SUMMARY and select Age. Note that interesting results are highlighted (these are the results of automatic statistics tests).
- To show the number of observations in each cell of the table, right-click on the table and select Statistics - cells > n.
Filtering the data
To filter the table to only show the data of males in full-time work:
- Follow the steps above to create a crosstab (or, if the crosstab has already been created, go select it).
- Press Home > Data Selection > New Filter.
- Type Gender in the First variable box and select it.
- Type Work Status in the Second variable box and select it.
- Check the Male and Fulltime worker cell.
- Press Create Filter. This causes the filter to be created. However, it does not apply it to the selected cells.
- Select the tables and/or plots you wish to filter (you can select multiple pages at the same time).
- Select the filter from Home > Data Selection > Filter.
To produce a of the proportion of people that said they Strongly agree or Agree a little with the statement Technology is fascinating:
- Click on the Attitudes tab (left of the screen).
- Press Crosstabs (on the left of the screen).
- Hold down your Shift button and select Strongly Agree and Agree a little.
- Press Data Manipulation > Rows/Columns > Create NET.
- Select 'Strongly agree + Agree a little and press Data Manipulation > Rows/Columns > Rename.
- Enter NET AGREE and press OK.
- Click on NET AGREE and drag it to the left of the table.
Re-basing involves recomputing the percentages on the table with some categories removed. In the above example the total sample size is 498 which includes two people that said DON'T KNOW. A more useful calculation of NET AGREE would remove these two respondents. This is done in DataCracker by:
- Follow the steps above to create a crosstab (or, if the crosstab has already been created, select it).
- Click on the category that you wish to exclude.
- Press Data Manipulation > Data Values > Missing Values.
- For DON'T KNOW select Exclude from analyses'.
- Press OK.
A crosstab can be shown as a basic chart by clicking on Home > Chart and selecting the desired chart:
This example shows how to change data from appearing as categorical to instead appearing as numeric:
- Click on the How many SMS sent in typical week tab.
- Data Manipulation > Structure > Average.
Computing minimums, medians and maximums
- Select a table that is showing an average (e.g., see the previous section).
- Home > Statistics Cells > Median.
- Home > Statistics Cells > Minimum.
- Home > Statistics Cells > Maximum.
Recoding numeric data
In the above example the range goes from 0 to 200 calls per week with a median of 3. This suggests that only a very small number of respondents have given high ratings and there may be advantage in recoding some of the higher values to lower values (so that they become less influential as outliers. We can do this by;
- Select a table containing the data we wish to recode.
- Data Manipulation > Data Values > Recode Values.
- Replace all the values greater than 50 with the value of 50.
- Press OK.
Simple predictive model
This example predicts the number of SMS (text messages) by demographics, assuming that you have recoded the data as numeric (see the previous section):
- Insert > Predictive Tree
- Select How many SMS sent in typical week.
- Work status
- Choose Show more patterns.
- Press Create Predictive Tree. You should get a tree that looks like this:
Creating market segments
In this section of the tutorial we will create some market segments using Latent Class Analysis:
- Create a new page (Insert > Pages > New Page > Table/Chart
- Insert > Analysis > Groups/Segments
Reporting and sharing results
The report can be exported to PowerPoint, as PDFs, as images and as online reports by clicking the appropriate icons from the ribbon.