Math 216: Statistical Thinking
Population
Sample
Variables
Inference
To eliminate sampling bias, always take a RANDOM SAMPLE!
Even with a random sample, data can still be biased, especially when collected on humans.
Some forms of bias to watch out for in data collection:
A random sample was asked: “Should there be a tax cut, or should money be used to fund new government programs?”
Tax Cut | Programs |
---|---|
60% | 40% |
A different random sample was asked: “Should there be a tax cut, or should money be spent on programs for education, the environment, health care, crime-fighting, and military defense?”
Tax Cut | Programs |
---|---|
22% | 78% |
Ann Landers column asked readers “If you had it to do over again, would you have children?”
The first request for data contained a letter from a young couple which listed worries about parenting and various reasons not to have kids.
\[30\% \text{ said yes}\]
The second request for data was in response to this number, in which Ann wrote how she was “stunned, disturbed, and just plain flummoxed.”
\[95\% \text{ said yes}\]
When respondents are either unable or unwilling to respond to your survey, this results in non-response bias.
An observational study is a study in which the researcher does not actively control the value of any variable but simply observes the values as they naturally exist.
An experiment is a study in which the researcher actively controls one or more of the explanatory variables.