Collecting data from every member of a population is the most accurate way of gathering information, but it is not always the most practical and can be very expensive. Typically, a sample survey is instead done on a subset of the population to make it quicker and less expensive.
When summarizing the data, we use different terms if the data came from a sample or the whole population.
If a survey is not representative of the entire population, we say that the survey has bias. There are a number of potential sources of bias that we should avoid:
Poor sampling techniques: If the people being surveyed do not resemble the population, the survey is likely to be biased.
Too small of a sample: In general, the bigger the number of people being surveyed, the closer the results will be to a census.
Poor question wording: The question asked should answer the purpose of the study.
Using loaded or leading questions: Avoid questions which use emotive language or might otherwise influence the results of the survey.
When we want to draw conclusions based on a collection of data, there are two methods that can be used: an observational study and an experiment.
When conclusions are drawn, we can assess the validity by considering the Law of Large Numbers.
Mario surveyed 20 students from his math class to find out whether students at his school think they should make statistics a mandatory class. 70\% of students said yes, and 30\% of students said no. The school has 3000 students.
State if 70\% is a statistic or parameter. Explain how you know.
State the method that Mario used to gather data. Explain your reasoning.
State some potential sources of bias in this survey.
Write an invalid conclusion based on Mario's survey results. Explain why the claim is invalid.
Mario's school has 3000 students. Using the Law of Large Numbers in your reasoning, explain why or why not you think Mario's sample is representative of the entire population.