Question

Why is it important to eliminate bias in a study? What effect(s) do different variables have on an experiment that they don't have on an observational study or survey? Describe the differences between these types of statistical studies.

Answer 1

Bias must be eliminated in a study to ensure accurate results. Variables have different effects on experiments compared to observational studies and surveys.

Step-by-step explanation:

It is important to eliminate bias in a study because bias can lead to inaccurate or misleading results. Bias occurs when certain factors or opinions influence the research process or the interpretation of data, resulting in a skewed representation of the truth. By eliminating bias, researchers can ensure that their findings are objective and reliable.

In an experiment, different variables can be manipulated and controlled to determine their effect on the outcome. This allows researchers to establish cause-and-effect relationships between variables. In an observational study or survey, however, variables are only observed or measured without any manipulation. This limits the ability to establish causality but allows for the exploration of associations or correlations between variables.

Overall, the main difference between experimental and observational studies lies in the level of control over variables. Experimental studies provide more control, allowing researchers to establish causality, whereas observational studies focus on observing relationships and associations between variables.