This section describes how to use derived variables to recategorise and transform survey data into new variable types, for example: combine categories within a Multi Choice variable, and convert numeric, date and time and literal data into categories.
- Calculating the difference between times on different dates
- Analysing dates
- Analysing post codes and zip codes
- Using patterns to categorise postcodes in to postal area
Online user guide and documentation
- Using derived variables
- Derived single variable
- Derived multiple variable
- Derived quantity variable
- Derived date variable
- Derived time variable
- Derived literal variable
- Categorising respondents by age and gender
- Categorising respondents by age and gender for a quota
- Categorising respondents by case number
- Categorising literals
- Categorising literals in Other field to add to multichoice list
- Adding text to a derived literal to create a readable list
- Using a derived variable with a pattern to categorise postcodes
- Categorising quantity responses with a derived variable
- Using derived variables to perform calculations
- Calculating age from a date of birth
- Calculate the interval between two times
- Categorising time responses into hourly periods
- Categorising date responses into six monthly periods
- Categorising date responses into days of the week
- Using a derived variable to weight the responses to a survey
- Using a derived variable to calculate mean scores
Training and consultancy
Our Analysing Results course will give you an introduction to using derived variables for analysis.
If you would like one-to-one training, we also offer online or face-to-face consultancies. Call us now on 01454 280820603-610-8700 or email us your training requirementsemail us your training requirements and we’ll call you back.
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