Just because every woman on the planet wasn't included in the study doesn't mean the study is invalid. Saying a study is wrong just because it doesn't include everyone is a weak argument. No study in history has ever included every single person, and that doesn't make their findings any less true. It would be impossible to study billions of people, so researchers select a representative sample that reflects different ages, races, social backgrounds, and other factors. If the sample is diverse, random, and large enough, the results can accurately show how common certain biases are in society. The study must also support external validity, meaning the results can be generalized to the broader population. With a sample large enough, the findings are likely to be statistically significant, meaning the results are unlikely to be due to random chance. This also reduces sampling error, the natural variation between the sample and the population. The confidence interval will further show how precise the results are. This method is used to study everything from diseases to social issues, proving that even a smaller sample can be predictive and provide valuable insights into a larger population.
