How do you identify if the sample data is biased or not and

How do you identify if the sample data is biased or not and how will you overcome it. The only info

availabe to use is the actual data, regression analsis, descriptive stats and some hypothesis tests

PS: Any sample data from population can be used

Solution

A sampling method is called biased if it systematically favors some outcomes over others. Sampling bias is sometimes called ascertainment bias (especially in biological fields) or systematic bias.

Bias can be intentional, but often it is not. The following example shows how a sample can be biased, even though there is some randomness in the selection of the sample.

Example:

Telephone sampling is common in marketing surveys. A simple random sample may be chosen from the sampling frame consisting of a list of telephone numbers of people in the area being surveyed. This method does involve taking a simple random sample, but it is not a simple random sample of the target population (consumers in the area being surveyed.) It will miss people who do not have a phone. It may also miss people who only have a cell phone that has an area code not in the region being surveyed. It will also miss people who do not wish to be surveyed, including those who monitor calls on an answering machine and don\'t answer those from telephone surveyors. Thus the method systematically excludes certain types of consumers in the area.

How can we know if the sample is biased?

Sometimes you can identify sampling bias just by being very thoughtful and comparing the characteristics of respondents in your sample to what you know about the population in general. Think about the demographic characteristics that might have an important relationship to their answers. For example, if you know that gender is an important variable, and you know that the population includes 50% males and 50% females, then the sample needs to include the same proportions. If the sample includes 20% males, your results are likely to be biased because you don