Ethics in Statistical Analysis and Reporting - University Statistics

This report provides an overview of ethics in statistical analysis and reporting, highlighting potential pitfalls such as data manipulation and biased data collection. It emphasizes the importance of objectivity and transparency in research to avoid misrepresentation of findings. The report underscores the need for researchers to maintain confidentiality and privacy while accurately interpreting data for the benefit of report readers. It concludes that ethics in statistics is crucial for ensuring the integrity and reliability of research outcomes.

Running head: BASIC BUSINESS STATISTICS
Basic Business Statistics
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1BASIC BUSINESS STATISTICS
Table of Contents
Introduction:....................................................................................................................................2
Ethics in statistical analysis and reporting:......................................................................................2
Conclusion:......................................................................................................................................3
References:......................................................................................................................................4

2BASIC BUSINESS STATISTICS
Introduction:
There are ethics in statistics like other areas, which a researcher needs to follow for
reporting truth and avoiding data misrepresentation. Certain number of ways are inherent that
might lead to arousal of unethical behaviour in statistics. This is because it is relatively easy to
manipulate data projecting the desired outcomes, while hiding the actual interpretation of the
numbers. However, this does occur every time and there is no reason of not believing in the
inference of a statistical analysis. Thus, the current report aims to evaluate the ethics in statistical
analysis and reporting.
Ethics in statistical analysis and reporting:
Ethics in statistics is not straightforward at all and it could be complex on certain
occasions. It relies on the type of statistical analysis conducted (Gelman and Price 2014).
Unethical behaviour might take place at any point from data collection to data interpretation. For
instance, collection of data could be made inherently biased by posing the incorrect questions
stimulating strong emotions, instead of objective realities. This takes place every time when the
survey is intended to try and prove a point of view, instead of finding out the truth. The other
unethical behaviours might constitute of scientists excluding data outliers in their report and
evaluation for validating their viewpoint. This occurs in social as well as pure sciences (Gelman
2017). By obscuring data reinforcing a specific theory, scientists are involving in unethical
behaviour.
Ethics in statistics are highly significant during representation of data as well. It has been
observed that the numbers do not lie; however, their representation and interpretation could be
misleading. For instance, after a wide survey of numerous customers, an organisation might

3BASIC BUSINESS STATISTICS
publish the figures and numbers reflecting well on it; however, it might fully neglect or not
provide due significance to other figures (Gelman 2013).
For instance, a car might be ranked greater on comfort; however, low on safety. By
depicting the comfort figures for the car, the organisation is misleading customers and
shareholders regarding the actual picture. In addition, polls and surveys often involve in
unscrupulous behaviour for reinforcing a point of view. For instance, a survey might not depict
the actual public opinion, since it is not statistically significant. However, numerous surveys do
not issue the same along with the poll and this could be misleading (Rosnow and Rosenthal
2014). Hence, as a researcher, objectivity is necessary and an overall picture obtained from the
experiment without hiding any detail for personal benefits needs to be provided. Thus, ethics in
statistics are significant to provide the correct direction to research for ensuring truth and
objectivity.
Conclusion:
From the above evaluation, it has been found that the researchers and scientists need to be
careful while representing the figures and numbers. They need to ensure confidentiality and
privacy at all cost for avoiding misuse of the same. Thus, objectivity needs to be assured in
statistical analysis and reporting, while interpreting the figures and numbers in an accurate
manner for presenting rightful information to the readers of the reports.

4BASIC BUSINESS STATISTICS
References:
Gelman, A. and Price, P.N., 2014. Ethics and Statistics: The Commissar for Traffic Presents the
Latest Five-Year Plan. CHANCE, 27(2), pp.58-60.
Gelman, A., 2013. Ethics and Statistics: They'd Rather Be Rigorous Than Right. Chance, 26(2),
pp.45-49.
Gelman, A., 2017. Ethics and Statistics: Honesty and Transparency Are Not
Enough. Chance, 30(1), pp.37-39.
Rosnow, R.L. and Rosenthal, R., 2014. Quantitative methods and ethics. The Oxford Handbook
of Quantitative Methods: Foundations, 1, p.32.