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Shared Professional Values

 

Our shared professional values are respect, professionalism, truthfulness and integrity.

 

1. Respect

We respect the privacy of others and the promises of confidentiality given to them.

We respect the communities where data is collected and guard against harm coming to them by misuse of the results.

We should not suppress or improperly detract from the work of others.

 

2. Professionalism

The value Professionalism implies Responsibility, Competence and Expert Knowledge, and Informed Judgment.

We work to understand our users’ needs.

We use our statistical knowledge, data, and analyses for the Common Good to serve the society.

We strive to collect and analyze data of the highest quality possible.

We are responsible for the fitness of data and of methods for the purpose at hand.

We discuss issues objectively and strive to contribute to the resolution of problems.

We obey the law and work to change laws we believe impede good statistical practice.

We are continuously learning both about our own field as well as those to which we apply our methods.

We develop new methods as appropriate.

We do not take assignments in which we have a clear conflict of interest.

We act responsibly with our employers.

 

3. Truthfulness and Integrity

By Truthfulness and Integrity, we mean Independence, Objectivity and Transparency.

We produce statistical results using our science and are not influenced by pressure from politicians or funders.

We are transparent about the statistical methodologies used and make these methodologies public.

We strive to produce results that reflect the observed phenomena in an impartial manner.

We present data and analyses honestly and openly.

We are accountable for our actions.

We have respect for intellectual property.

As scientists, we pursue promising new ideas and discard those demonstrated to be invalid.

We work towards the logical coherence and empirical adequacy of our data and conclusions.

We value well-established objective criteria of assessment.

 

 

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