Let’s look at how to create complex calculations!
How to Create Complex Calculations: AND/OR
or any questions for which you’re not using the “VALUE” you can use the “AND/OR” function.
“AND” and “OR” are logical operators. They are used to combine two or more questions to produce a single result based on whether the conditions are true or false.
The “AND” operator returns true only if both conditions are true. So, if an individual respondent in your survey meets both conditions they will be included in your result, if they don’t meet both conditions they will not be included in your result.
The “OR” operator returns true if either one of the conditions is true. So, if an individual respondent in your survey meets one condition they will be included in your result, if they don’t meet either conditions they will not be included in your result.
If you AND/OR in calculating an indicator the result will be the # or % of the “true” (those who meet the conditions) in your sample. If you use this for filtering or disaggregation, only those that resulted in “true” will be used in the calculation.
Below are two examples, the first using the “AND” and the second using “OR”:
- In the example below, we use “AND” to create a disaggregation for women under 18, by setting the condition for age to be below (<) 18, and gender to be “Female” (e.g. the total number of Females under 18 years of age as seen in the first row):


2. In this second example, we use the “OR” operator to filter the calculation only for those who are younger than 18 or older than 60 years of age:

Note: To calculate the opposite of the “OR” example above, you can use the “between” function to calculate those between the ages of 18 and 60.

How to Create Complex Calculations: – *
To calculate values from multiple questions you can use the (plus), – (minus), * (multiply) or / (divide) operations.
In this example below, you can see that we have combined the data from two age groups to create a larger age group. Here we have added the age groups “18-25” and “26-30” to create one larger age group in our disaggregation: “18-30”.

Note: If you want to calculate, for example, the total % of female participants in your trainings when using a training tracking sheet (where one data row is one training) from separately recorded values of “# of female participants” and “Total # of participants” (i.e. “# of female participants” / “Total # of participants”). You cannot calculate this in Kinaki using the calculation “# of female participants” / “Total # of participants” because Kinaki would calculate this proportion for each of the trainings and then it would average out these proportions, without taking into account how many participants each training has and this result would be incorrect. If you need to get such a proportion we recommend creating two disaggregation lines, one for “# of female participants” and one for “Total # of participants” and then calculating the proportion in the exported report manually.
If you track individual participants of the training, so if in your data each row is one participant, then you can calculate this proportion by simply adding the gender question with “female” selected to the “Calculate results for” field.