Which of the following would be used to describe the type of statistical methods used to organize and describe the characteristics of a collection of data quizlet?

Prepared by the Committee on Professional Ethics of the American Statistical Association
Approved by ASA Board of Directors February 1, 2022

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Purpose of the Guidelines

The American Statistical Association’s Ethical Guidelines for Statistical Practice are intended to help statistical practitioners make decisions ethically. In these guidelines, “statistical practice” includes activities such as designing the collection of, summarizing, processing, analyzing, interpreting, or presenting data and model or algorithm development and deployment. Throughout these guidelines, the term “statistical practitioner” includes all those who engage in statistical practice, regardless of job title, profession, level, or field of degree. The guidelines are intended for individuals, but these principles are also relevant to organizations that engage in statistical practice.

The ethical guidelines aim to promote accountability by informing those who rely on any aspects of statistical practice of the standards they should expect. Society benefits from informed judgments supported by ethical statistical practice. All statistical practitioners are expected to follow these guidelines and encourage others to do the same.

In some situations, guideline principles may require balancing competing interests. If an unexpected ethical challenge arises, the ethical practitioner seeks guidance, not exceptions, in the guidelines. To justify unethical behaviors, or to exploit gaps in the guidelines, is unprofessional and inconsistent with these guidelines.

PRINCIPLE A: Professional Integrity and Accountability

Professional integrity and accountability require taking responsibility for one’s work. Ethical statistical practice supports valid and prudent decision-making with appropriate methodology. The ethical statistical practitioner represents their capabilities and activities honestly and treats others with respect.

The ethical statistical practitioner:


PRINCIPLE B: Integrity of Data and Methods

The ethical statistical practitioner seeks to understand and mitigate known or suspected limitations, defects, or biases in the data or methods and communicates potential impacts on the interpretation, conclusions, recommendations, decisions, or other results of statistical practices.

The ethical statistical practitioner:


PRINCIPLE C: Responsibilities to Stakeholders

Those who fund, contribute to, use, or are affected by statistical practices are considered stakeholders. The ethical statistical practitioner respects the interests of stakeholders while practicing in compliance with these guidelines.

The ethical statistical practitioner:


PRINCIPLE D: Responsibilities to Research Subjects, Data Subjects, or Those Directly Affected by Statistical Practices

The ethical statistical practitioner does not misuse or condone the misuse of data. They protect and respect the rights and interests of human and animal subjects. These responsibilities extend to those who will be directly affected by statistical practices.

The ethical statistical practitioner:


PRINCIPLE E: Responsibilities to Members of Multidisciplinary Teams

Statistical practice is often conducted in teams made up of professionals with different professional standards. The statistical practitioner must know how to work ethically in this environment.

The ethical statistical practitioner:


PRINCIPLE F: Responsibilities to Fellow Statistical Practitioners and the Profession

Statistical practices occur in a wide range of contexts. Irrespective of job title and training, those who practice statistics have a responsibility to treat statistical practitioners, and the profession, with respect. Responsibilities to other practitioners and the profession include honest communication and engagement that can strengthen the work of others and the profession.

The ethical statistical practitioner:


PRINCIPLE G: Responsibilities of Leaders, Supervisors, and Mentors in Statistical Practice

Statistical practitioners leading, supervising, and/or mentoring people in statistical practice have specific obligations to follow and promote these ethical guidelines. Their support for, and insistence on, ethical statistical practice are essential for the integrity of the practice and profession of statistics, as well as the practitioners themselves.

Those leading, supervising, or mentoring statistical practitioners are expected to:


PRINCIPLE H: Responsibilities Regarding Potential Misconduct

The ethical statistical practitioner understands that questions may arise concerning potential misconduct related to statistical, scientific, or professional practice. At times, a practitioner may accuse someone of misconduct or be accused by others. At other times, a practitioner may be involved in the investigation of others’ behavior. Allegations of misconduct may arise within different institutions with different standards and potentially different outcomes. The elements that follow relate specifically to allegations of statistical, scientific, and professional misconduct.

The ethical statistical practitioner:


APPENDIX
Responsibilities of Organizations/Institutions

Whenever organizations and institutions design the collection of, summarize, process, analyze, interpret, or present data or develop and/or deploy models or algorithms, they have responsibilities to use statistical practice in ways that are consistent with these guidelines, as well as to promote ethical statistical practice.

Organizations and institutions engage in and promote ethical statistical practice by:

Those in leadership, supervisory, or managerial positions who oversee statistical practitioners promote ethical statistical practice by following Principle G and:

Which of the following statistical methods used to describe the characteristics of a sample?

Inferential statistics use the characteristics in a sample to infer what the unknown parameters are in a given population. In this way, as shown in Figure 1.2, a sample is selected from a population to learn more about the characteristics in the population of interest.

Which of the following refers to the type of statistical methods used to draw conclusions about the population based on a sample?

The process of using sample statistics to make conclusions about population parameters is known as inferential statistics.

Which of the following are characteristics of a descriptive statistical study?

There are three essential characteristics of descriptive statistics we need to discuss: scales of measurement, measures of central tendency, and measures of variability (or spread).

Which type of statistics helps us organize and describe data collected from a specified population?

Descriptive statistics provides us the tools to define our data in a most understandable and appropriate way. It is about using data from sample and then making inferences about the larger population from which the sample is drawn.

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