Proposito De Las Directrices En Estadistica

1. PREAMBLE

A. PURPOSE OF THE GUIDELINES

The American statistical association’s ethical guidelines for statistical practice are intended to help statistical practitioners make and communicate ethical decisions. Clients, employers, researchers, policy makers, journalists, and the public should be urged to expect that statistical practice will be conducted in accordance with these guidelines and to object when it is not. While learning how to apply statistical theory to problems, students should be encouraged to use these guidelines whether or not their target professional specialty will be “statistician”. Employers, attorneys, and other clients of statistical practitioners have a responsibility to provide a moral environment that fosters the use of these ethical guidelines.

Application of these or any other ethical guidelines generally requires good judgment and common sense. The guidelines may be partially conflicting in specific cases. the application of these guidelines in any given case can depend on issues of law and shared values, work-group politics, the status and power of the individuals involved, and the extent to which the ethical lapses pose a threat to the public, to one’s profession, or to one’s organization. The individuals and institutions responsible for making such ethical decisions can receive valuable assistance by discussion and consultation with others, particularly persons with divergent interests with respect to the ethical issues under consideration.

B. STATISTICS AND SOCIETY

The professional performance of statistical analyses is essential to many aspect of society. The use of statistics in medical diagnoses and biomedical research may affect whether individuals live or die, whether their health is protected or jeopardized, and whether medical science advances or gets sidetracked. Life, death, and health, as well as efficiency, may be at stake in statistical analyses of occupational, environmental, or transportation safety. Early detection and control of new or recurrent infectious diseases depend on sound epidemiological statistics. Mental and social health may be at stake in psychological and sociological applications of statistical analysis.

Effective functioning of the economy depends on the availability of reliable, timely, and properly interpreted economic data. The profitability of individual firms depends in part on their quality control and their market research, both of which should rely on statistical methods. Agricultural productivity benefits greatly from statistically sound applications to research and output reporting. Governmental policy decisions regarding public health, criminal justice, social equity, education, the environment, the sitting of critical facilities, and other matters depend in part on sound statistical.

Scientific and engineering research in all disciplines requires the careful design and analysis of experiments and observations. To the extent that uncertainty and measurement error are involved—as they are in most research—research design, data quality management, analysis, and interpretation are all crucially dependent on statistical concepts and methods. Even in theory, much of science and engineering involves natural variability. Variability, whether great or small, must be carefully examined both for random error and for possible researcher bias or wishful thinking.

Statistical tools and methods, like many other technologies, can be employed either for social good or for evil. The professionalism encouraged by these guidelines is predicated on their use in socially responsible pursuits by morally responsible societies, governments, and employers. Where the end purpose of a statistical application is itself morally reprehensible, statistical professionalism ceases to have ethical worth.

C. SHARED VALUES

Because society depends on sound statistical practice, all practitioners of statistical, whatever their training and occupation, have social obligations to perform their work in a professional, competent, and ethical manner. This document is directed to those whose primary occupation is statistics. Still, the principles expressed here should also guide the statistical work professionals in all other disciplines that use statistical methods. All statistical practitioners are obliged to conduct their professional activities with responsible attention to:

1. the social value of their work and the consequences of how well or poorly it is performed. This includes respect for the life, liberty, dignity, and property of other people.

2. The avoidance of any tendency to slant statistical work toward predetermined outcomes. (it is acceptable to advocated a position; it is not acceptable to misapply statistical methods in doing so.)

3. Statistics as a science. (as in any science, understanding evolves. Statisticians have a body of established knowledge but also many unresolved issues that deserve frank discussion).

4. The maintenance and upgrading of competence in their work.

5. Adherence to all applicable laws and regulations, as well as applicable international covenants, while also seeking to change any of those that are ethically inappropriate.

6. Preservation of data archives in a manner consistent with responsible protection of the safety and confidentiality of any human beings and organizations involved.

In addition to ethical obligations, good professional citizenship encourages:

7. Collegiality and civility with fellow professionals.

8. Support for improved public understanding of and respect for statistics.

9. Support for sound statistical practice, especially when it is unfairly criticized.

10. Exposure of dishonest or incompetent uses of statistics.

11. Service to one’s profession as a statistical editor, reviewer, or association official and service as an active participant in (formal or informal) ethical review panels.

II.ETHICAL GUIDELINES

A. PROFESSIONALISM

1. Strive for relevance in statistical analyses. Typically , each study should be based on a competent understanding of the subject matter issues, statistical protocols that are clearly defined for the stage ( exploratory, intermediate, or final) of analysis before looking at those data that will be decisive for that stage, and technical criteria to justify both the practical relevance of the study and the amount of data to be used.

2. Guard against the possibility that a predisposition

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