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Lesson

Lesson 5: Stratified Random Sampling

12 September 2022

Stratification improves precision by reducing the chances of ‘unlucky’ samples. You almost always want to stratify if you have any data on individuals in your sampling frame in advance.

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Navigating the next frontier: Doing more with less in West and North Africa

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Bringing implementation science to AI: The case for process evaluations in the AI evaluation framework

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Adapting for impact: Reflecting on a year of uncertainty and reinvention

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Lessons from IDinsight’s Generative AI transformation

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Building a right-fit data infrastructure to support SOIL’s program scalability

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Improving nutrition investments through cost-effective feeding models

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Life Skills Collaborative

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Powering change: MCA-Sénégal II Electricity Compact & IDinsight’s learning agenda to support economic growth in Senegal

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