What are the best ways to ensure your sample is representative?

I follow the United Nations Economic and Social Council's (ECOSOC) approach to ensuring sample representativeness, which involves clearly defining the target population. For instance, when conducting a survey on global sustainable development goals, ECOSOC meticulously outlines the specific demographic, geographic, and socio-economic characteristics of the population of interest. This precision helps in selecting a sample that accurately mirrors the diversity within the larger population, ensuring that the findings are both meaningful and applicable on a broader scale.

This is one of the most integral parts of the process. Operationalize, operationalize, operationalize! In the example used in the article, we are defining what it means to be a "small business". This can mean many things to many people, and that meaning has the potential to greatly impact your findings. Here are some ways to get clear on your population definitions: 1. Grab a piece of paper and set a timer for two minutes- jot down all the criteria that come to mind for a "small business". 2. Look up how other researchers have defined your population. 3. Get feedback from others! You may have a bias or mental block about the subject. Spending quality time on this step saves a lot of complex data scrubbing and whoopsies later on!

I admire the United Nations' approach to ensuring representative samples through stratified random sampling. For instance, in conducting global surveys on education, the UN may stratify countries based on income levels, ensuring proportional representation of low, middle, and high-income nations. This method helps capture diverse perspectives, mitigating biases and providing a more accurate reflection of the global education landscape.

We should calculate our sample size meticulously to ensure it is representative of the population. Utilizing statistical methods such as random sampling and stratified sampling helps minimize biases and ensures diverse inclusion. An exemplary application is the United Nations Population Fund (UNFPA) conducting surveys on reproductive health. By employing rigorous sampling techniques, like stratification based on geographical regions and demographic characteristics, the UNFPA ensures that its collected data accurately reflects the diverse perspectives and needs of populations worldwide, enhancing the reliability and applicability of their findings.

We should monitor our response rate to ensure our sample is representative. For instance, the United Nations (UN) regularly employs this strategy in surveying member states to gauge global opinions and perspectives on critical issues. By tracking and analyzing response rates, we can identify and address potential biases, ensuring a more accurate reflection of the diverse viewpoints within the surveyed population.