What is the best way of choosing a sample to statistically represent a population? Why? What is a biased sample? How can biased sampling affect the statistical study of a population?
Search the Internet and give two or more real-world examples of biased sampling leading to unexpected or unfavorable outcomes. In each case, how could the sample have been improved to make a more accurate inference about the population?
any unwanted answers will be reported
Share
Step-by-step explanation:
In a simple random sample, every member of the population has an equal chance of being selected.
Your sampling frame should include the whole population. To conduct this type of sampling, you can use tools like random number generators or other techniques that are based entirely on chance.
Biased sample
A sample is biased if individuals or groups from the population are not represented in the sample.
In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population have a lower or higher sampling probability than others.
Affects
It affects the internal validity of an analysis by leading to inaccurate estimation of relationships between variables. It also can affect the external validity of an analysis because the results from a biased sample may not generalize to the population.
Answer:
In random sampling, the whole population should have an equal chance of being chosen.
You can use something like every third person or a random number generat
Step-by-step explanation: