Animal Behavior Reliability
  • Home
  • About
  • Foundations
    • Proposal
    • Measurements >
      • Definitions
    • Team makeup
    • Training >
      • Features of test subsets
      • Assessment
    • Metrics
  • Diving deeper
    • Iterative training processes >
      • Tasks and techniques
      • Categorical data
      • Continuous data
      • Rare outcomes
    • Timeline
    • Troubleshooting
    • Reporting
  • Checklist
  • Resources

Diving Deeper.

The reliability process can be complex. At this point, we assume that you are familiar with the topics covered under Foundations, and are ready to take a deeper dive into the training, evaluating, and troubleshooting process.

Iterative training processes

The reliability training process can differ depending on the type of data you're collecting. We have different iterative processes that we follow for tasks, categorical data, and continuous data. We also sometimes run into challenges when our outcomes of interest are rare and have a separate process for this situation. Click below to learn more about each process.

Tasks and techniques

Categorical data

Continuous data

Rare outcomes

Troubleshooting

Regardless of the type of data, reliability training often requires troubleshooting. When we troubleshoot, we identify the problem, diagnose it, and take actionable steps to fix it. This process can be challenging, and time-consuming, but is fundamental to our philosophy.

Here, we lay out some structure and orientation to what troubleshooting looks like for us, along with some common examples of problems that come up in behavior reliability. 
Learn more ->

Reporting

After creating, analyzing, and troubleshooting your reliability training, you then need to report this information in your publications. Here, we describe what we consider best practice and provide examples of how we report our metrics.
Learn more ->
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  • Home
  • About
  • Foundations
    • Proposal
    • Measurements >
      • Definitions
    • Team makeup
    • Training >
      • Features of test subsets
      • Assessment
    • Metrics
  • Diving deeper
    • Iterative training processes >
      • Tasks and techniques
      • Categorical data
      • Continuous data
      • Rare outcomes
    • Timeline
    • Troubleshooting
    • Reporting
  • Checklist
  • Resources