Parameters are the building blocks of your data tracking in the app. They define what kind of data you want to track and how this data behaves. To get the most accurate and meaningful insights, it’s essential to set up your parameters correctly

Parameter Types

1. Binary – A simple yes or no choice. Use this when you only need to record if something happened or not.
   • Examples: “Rained”, “Success”, “Meditated”, “Slept well”
2. Ordinal – A ranked scale from 0 to N (max 2,147,483,647), defined by the user. Use this for abstract ranges where the order matters but the difference between levels is not necessarily equal.
   • Examples: Mood level (0-5), productivity level (0-7), pain intensity (0-10)
3. Quantitative – Any measurable value, including decimals (IEEE 754, double precision). Use this for precise, continuous measurements.
   • Examples: Temperature (°C/°F), water consumed (ml), steps walked, kilometers run

Parameter Roles

Parameters can also play different roles based on how their data should be interpreted:

1. Instant – Measurements that capture a single moment or state, not meant to be summed. The more measurements you take, the more accurate the analysis, but adding them up doesn’t make sense.
   • Examples: Temperature, heart rate, air quality index
2. Cumulative – Measurements that naturally add up over time. Summing these values gives a meaningful total for a period.
   • Examples: Water consumed, calories burned, hours practiced
3. Accumulated – Data that is already a running total, typically from external sources like fitness trackers. Adding these values again doesn’t make sense.
   • Examples: Total steps from a pedometer, total distance covered from a GPS tracker

Changing Roles and Types

• You can change the role of a parameter at any time to reflect different analysis approaches as your data evolves.
• However, the type of a parameter cannot be changed once data has been added, as converting between types is generally not feasible.
• If you need to change the type, you can create a new parameter with the desired type, manually transfer the data, and then remove the old parameter.

Data Aggregation and Correlation

Different correlation formulas apply to different parameter types, and daily data aggregation methods depend on the parameter roles. While the app will do its best to interpret your data, accurate setup leads to better results. Cooperation is key to meaningful insights!

Automatically Filled Parameters

The app also provides a few parameters that are automatically recorded:

• Hour of Day (Type: Numerical, Role: Instant) – The exact hour when the sample was added.
• Samples per Day (Type: Numerical, Role: Cumulative) – The total number of samples added on a given day.
• Hours from Previous Sample (Type: Numerical, Role: Instant) – The time difference from the previous sample.

These built-in parameters can be used for tracking and correlation analysis just like user-defined parameters, but they cannot be edited directly.

Properly setting up your parameters ensures that your insights are as accurate and meaningful as possible. Take the time to consider the types and roles that best match the data you want to track. Happy tracking!