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The most common procedure to reduce the risk of confounding variables (and thus increase internal validity) is random assignment of participants to levels of the independent variable.

21 / 01 / 2019 Others

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Control internal validity

The most common procedure to reduce the risk of confounding variables (and thus increase internal validity) is random assignment of participants to levels of the independent variable. This means that each participant in a study has an equal probability of being assigned to any of the levels of the independent variable. Bill Altermatt, 2010
Define and describe sampling bias with example:
Bias is a systematic error that can prejudice your evaluation findings in some way. So, sampling bias is consistent error that arises due to the sample selection. For example, a survey of high school students to measure teenage use of illegal drugs will be a biased sample because it does not include home schooled students or dropouts. A sample is also biased if certain members are underrepresented or overrepresented relative to others in the population. For example, distributing a questionnaire at the end of a 3-day conference is likely to include more people who are committed to the conference so their views would be overrepresented. Interviews with people who walk by a certain location are going to over-represent healthy individuals or those who live near the location. Selecting a sample using a telephone book will underrepresent people who cannot afford a telephone, do not have a telephone, or do not list their telephone numbers.
Sampling bias can occur any time your sample is not a random sample. If it is not random, some individuals are more likely than others to be chosen.
Define and describe experimenter bias with example:
Experimental bias is where the scientist or researcher doing the research influences the results so that they can show a certain outcome. The expectation of the experiment can be subtly communicated to the person doing the experiment. Experimental bias arises where there could be experimental errors or where all possible variables were not taken into account.

 

1- Ellen Taylor-Powell, Evaluation Specialist, Program Development and Evaluation,
University of Wisconsin-Extension, Cooperative Extension, 6-2009.


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