Analysis of Validity, Reliability, and Ethical Issues in Statistics

This assignment addresses the concepts of validity and reliability in statistical research, highlighting potential ethical challenges. It discusses how the design of a research study, selection of sample sizes, and the choice of measurement tools can impact the validity and reliability of findings. The assignment also explores technical approaches to enhance validity and reliability, such as improving measurement techniques, controlling variables, and increasing randomization to reduce bias. Furthermore, it provides guidance on how to handle situations where research findings become politicized, suggesting methods like consulting stakeholders and seeking alternative explanations. References to relevant literature are included to support the arguments presented.

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Solution
Potential ethical “mine fields” in the area of validity and reliability
Validity and reliability are concepts used in research to examine the quality of research
by giving an explanation of how well methods, techniques or tests applied measure something.
Validity encompasses the accuracy while reliability involves the consistency of the measure.
However, there are potential ethical “mine fields” in the areas of validity and reliability (Wagner,
2016). These are areas that have a lot of hidden dangers or problems, and where evaluators to be
careful to avoid being wrong and hence their analysis and results posing ethical threat.
The “mine fields” include; design of the research study, sample size selection, selection
of measurement tools and choosing of appropriate methods and techniques to meet the threshold
of validity and reliability. Researchers who do not design their research appropriately or do not
decide their sample sizes correctly have a higher probability of not meeting the validity and
reliability requirements. On the other hand, adoption of inappropriate tools, methods and
techniques could lead to potentially being unable achieve valid and reliable results leading to
bias (Skott & Ward, 2012).
Technical approaches an evaluator can take to enhance validity and reliability
There are different ways that an evaluator can take to enhance validity and reliability including
improvement of measurement techniques, controlling a large number of variables, having an
increased level of randomization to reduce bias, adding control and placeable groups and
blinding the experiment (Kara, 2015).
Improvement of measurement techniques involves the adoption of technology such as
computers of sensors in measurement rather than relying on hand. It also involves relying on
multiple measurement sources rather than a single source. Controlling more variables involves

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ensuring that only a few things change in a test. For example, in a test to determine the rolling
speed of a ball down a steep hill, the mass of the ball can be changed and everything else kept
constant. The variables kept the same can include the material used in making the ball, the point
of releasing the ball, the location of ball release, the height above sea level, and humidity. As the
number of variables kept the same increases, the validity also increases. Lastly, increasing of
randomization can help reduce sample bias hence increase validity. For example, when testing a
vaccine for a particular disease and the sample selected comprised female kids between 4-5years,
this sample is not a good sample as it representative of entire population of kids in terms of age
and gender, thus the only way to reduce the bias is to increase randomization. If the findings of a
research become political, an evaluator can retake the research and ensure that in the new
research all stakeholders are consulted and multiple data sources used. Moreover, he can present
the results to other stakeholders to review and present their findings. He can also seek for
alternative explanations or review the findings with colleagues.

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References
Kara, H. (2015). Creative research methods in the social sciences: A practical guide. Policy
Press.
Skott, B. P., & Ward, M. (2012). Active learning exercises for research methods in social
sciences. SAGE.
Wagner, C. (2016). Teaching research methods in the social sciences. Routledge.