Ethics & Statistics
Andew Gelman and David Madigan touch on the ethical dimensions of Statistics in How is Ethics like
Logistic regression is very similar to linear regression, except the response variable is categorical (yes/no), and not numerical. So, for example, a logistic regression model could take into account a variety of factors to determine whether we should implement a new medication, given the possible risks. In addition, a logistic regression could determine whether a homeowner is likely to default on a mortgage. This technique can be used to answer sensitive questions.
Often we need to make decisions in Statistics that might be considered unethical. Gelman and Madigan (2015) vividly claim “In general, though, the most informative ethics vignettes are those in which the call is not so close as to seem arbitrary, but not so obvious that the decision can be made without thought”. The best Statistical problems are those where the decision is not easy to make and a wrong decision carries a hefty cost.
Do you think regression should be used to answer sensitive problems, where a wrong decision incurs great risk? How strong of a correlation do you think is enough for us to feel a certain decision is viable? Can Statistics ever provide certainty for us in decision making?
Sample Solution
Logistic regression is the appropriate regression analysis to conduct when the dependent variable is dichotomous (binary). Similar to all regression analyses, the logistic regression is a predictive analysis. Logistic regression is used to describe data and to explain the relationship between one dependent binary variable and one or more nominal, ordinal, interval or ratio-level independent variables.Sometimes logistic regressions are difficult to interpret; the Intellectus Statistics tool easily allows you to conduct the analysis, then in plain English interprets the output.
