If the sample is not representative of the population, then the characteristics
of the sample are not the characteristics of the population.
Example:
If I want to estimate the percentage of the population that are men, and my
sample is the school's football team, my estimate would be that 100% of the
population is comprised of men. What went wrong with my survey ? Simple.
The football team is not a representative sample of the population, at least
not as regards gender.
Wiki User
∙ 11y agoIt is important for a sample to be representative, so that the whole population's view is counted, and not biased by one particular group within the population.
Because without representative sample, your results will not be valid.
It helps you nawser
A sample that accurately reflects the characteristics of the population as a whole
Take a simple random sample.
It is important for a sample to be representative, so that the whole population's view is counted, and not biased by one particular group within the population.
To generalize results from the sample population to the target population.
Many statistical statements for a population which are based on a sample are not valid if the sample is not representative.
Because without representative sample, your results will not be valid.
A sample is any subset of the total population. A representative sample is one that is chosen so that its characteristics are similar to that of the population.
It helps you nawser
A representative sample is a randomly selected subset of the population.
A simple random sample.
It is called a representative sample.
A sample that accurately reflects the characteristics of the population as a whole
The most important step to ensure accuracy in a sample is random selection. By randomly choosing samples from the population, you minimize bias and increase the likelihood that your sample is representative of the entire population. This helps to draw reliable conclusions and make valid inferences based on the sample data.
Well, if your sample does not represent the larger sample, you'll certainly not get a valid result ... For example, if you're studying pregnancy and your sample includes men - The whole idea of "representative' sample is fuzzy and often gives interesting errors.