Whether you are working with existing data or generating your own, sampling is a deceptively complicated and anxiety-inducing process especially when participants are people. Pressured by the usual limitations on time, access, and resources, you can panic at the thought that sampling involves theory and calculations and make snap decisions that usually lead to convenience sampling and ultimately, weak research claims. This Fix takes the panic out of sampling designs and helps you understand what sampling is, how it applies to different types of situations, and how to decide what approach works best for your project so you can maximize the impact of your research. It covers questions like: · What is sampling? · What is my population? · Should I use probability sampling? · Should I use subjective, non-probability sampling? · How do I sample from ill-defined, hard-to-reach, and wary populations? · How can I sample people ethically? · How can I reduce error and bias in sampling? · How large should my sample be?
Whether you are working with existing data or generating your own, sampling is a deceptively complicated and anxiety-inducing process especially when participants are people. Pressured by the usual limitations on time, access, and resources, you can panic at the thought that sampling involves theory and calculations and make snap decisions that usually lead to convenience sampling and ultimately, weak research claims. This Fix takes the panic out of sampling designs and helps you understand what sampling is, how it applies to different types of situations, and how to decide what approach works best for your project so you can maximize the impact of your research. It covers questions like: · What is sampling? · What is my population? · Should I use probability sampling? · Should I use subjective, non-probability sampling? · How do I sample from ill-defined, hard-to-reach, and wary populations? · How can I sample people ethically? · How can I reduce error and bias in sampling? · How large should my sample be?
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