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  • Sampling - Yale University

    This course paper defines three different simplified sampling options.Contents Simple random sampling Stratified random sampling Multistage random sampling
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  • Measuring what matters (a thinking tool)

    Measuring what matters is a decision-support tool. It helps users select data collection methods based on:
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  • Decision making matrix - Word template

    A decision making matrix can be useful to summarise decision makers and types of decisions in a matrix which can be referred to when developing and implementing evaluation processes.
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  • VUE

    The Visual Understanding Environment (VUE) is a concept and content mapping application developed to support teaching, learning and research.
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  • Scapple

    Scapple is an easy-to-use tool for getting ideas down as quickly as possible and making connections between them.
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  • Adapting evaluation in the time of COVID-19 – Part 4: Describe

    We’re continuing our series, sharing ideas and resources on ways of ensuring that evaluation adequately responds to the new challenges during the pandemic.
    Blog
  • Formal meeting processes

    Studies have demonstrated that attendance at meetings and conferences, planning discussions within the project related to use of the program evaluation, and participation in data collection foster feelings of evaluation involvement among st
    Method
  • Sampling for surveys: Stratified random sampling

    These instructional videos provide a guide and examples of how to apply stratified random sampling.
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  • Sampling for surveys: Clustered random sampling

    These instructional videos provide a guide and examples of how to apply clustered random sampling.
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  • Sampling for surveys: Sample size calculations

    This instructional video explains how to calculate a sample size for a survey.
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  • Sampling for surveys: Simple random sampling

    These instructional videos introduce the topic of sampling for surveys and provide a guide and examples of how to apply simple random sampling.
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  • 6: Sample size and power calculations

    This presentation explores methods for identifying the right sample size for randomized evaluations so that results are defendable.
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