{"id":10729,"date":"2024-12-11T09:59:50","date_gmt":"2024-12-11T09:59:50","guid":{"rendered":"https:\/\/researcher.life\/blog\/?p=10729"},"modified":"2024-12-25T10:13:27","modified_gmt":"2024-12-25T10:13:27","slug":"population-vs-sample-difference-examples","status":"publish","type":"post","link":"https:\/\/researcher.life\/blog\/article\/population-vs-sample-difference-examples\/","title":{"rendered":"Population vs Sample – Difference and Examples\u00a0"},"content":{"rendered":"

\"population<\/p>\n

No matter what kind of research you are doing, and irrespective of the discipline you are studying, collecting and analyzing data correctly is key to ensuring that your findings are reliable. However, collecting data for research can be challenging and most people find themselves having to decide whether to collect data from an entire population or to use a smaller sample.\u00a0<\/span>\u00a0<\/span><\/p>\n

That is why understanding the <\/span>differences between population parameters and sample statistics<\/span> and knowing when to use each is an essential skill \u2013 required for drawing valid conclusions and ensuring that research outcomes are accurate, and relevant. This is important because inaccurate data can lead to wrong conclusions and, even worse, can damage the credibility of your research, wasting both time and resources.\u00a0<\/span>\u00a0<\/span><\/p>\n

Before we go further, let us try and understand what the terms population and sample mean from a research perspective.<\/span>\u00a0<\/span><\/p>\n

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