1. Section 15.1-1 Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series by Mario F. Triola

2. Section 15.1-2 Copyright © 2014, 2012, 2010 Pearson Education, Inc. Chapter 15 Ethics, Projects, Procedures, and Perspectives 15-1 Ethics in Statistics 15-2 Projects 15-3 Procedures 15-4 Perspectives

3. Section 15.1-3 Copyright © 2014, 2012, 2010 Pearson Education, Inc. Key Concept Statistical methods give us tremendous power to better understand the world, but this power can be abused in ways that are fundamentally unethical. We must consider some ethical issues related to data collection, analysis, and reporting.

4. Section 15.1-4 Copyright © 2014, 2012, 2010 Pearson Education, Inc. I. Data Collection “The end does not justify the means” is a widely quoted phrase center to many ethical debates. There are many research studies in which the health and safety of research subjects were compromised so that others might benefit. Prisoner Studies in the United States during the 1970s Milgram Experiment during the 1960s

5. Section 15.1-5 Copyright © 2014, 2012, 2010 Pearson Education, Inc. I. Data Collection Sampling Bias – some individuals are more or less likely to be included in a study, resulting in a sample that is not random. Sampling bias can seriously distort the interpretation of study results and result in wrong or misleading conclusions. Examples include “cherry picking,” nonrespondent bias, interviewer bias, and volunteer bias.

6. Section 15.1-6 Copyright © 2014, 2012, 2010 Pearson Education, Inc. II. Analysis Research study findings are often distorted by improper analysis. Many researchers succumb to pressures and temptations to report significant or “conclusive” results through negligent and unethical analysis.

7. Section 15.1-7 Copyright © 2014, 2012, 2010 Pearson Education, Inc. II. Analysis Falsified Data: According to one article, nearly 2% of scientists admitted to have fabricated, falsified, or modified data or results at least once. Inappropriate Statistical Methods: Whether intentional or unintentional, studies on this topic have shown that errors in statistical analysis are widespread.

8. Section 15.1-8 Copyright © 2014, 2012, 2010 Pearson Education, Inc. III. Ethics and Reporting Conflicts of Interest – Ghostwriting: A medical ghostwriter is someone who contributes to the writing of a research study or article but is not acknowledged in the published work. Conflicts of Interest – Financial Support: Pharmaceutical and medical device companies fund a substantial amount of medical research, which can skew the work and distort the findings.

9. Section 15.1-9 Copyright © 2014, 2012, 2010 Pearson Education, Inc. IV. Enforcing Ethics Many organizations have established ethical guidelines for their members or authors whose works they publish. The Common Rule: 1. People who participate as subjects are selected equitably and give their fully informed, fully voluntary written consent. 2. Proposed research is reviewed by an independent oversight group called an Institutional Review Board.

10. Section 15.1-10 Copyright © 2014, 2012, 2010 Pearson Education, Inc. IV. Enforcing Ethics As consumers of data, each of us should ponder the following questions: 1. Who is reporting the study and do they have any financial or personal interest in the outcome? 2. How were the data obtained? Are there potential biases? 3. Have these findings been reviewed by peers or anyone else? 4. What specifics do they provide about the methods used?

11. Section 15.1-11 Copyright © 2014, 2012, 2010 Pearson Education, Inc. IV. Enforcing Ethics As researchers, we should strive to behave ethically: 1. Be complete and honest about the findings. 2. Seek the advice of professionals when unsure about statistical methods. 3. Disclose financial relationships and any other interests in the outcome of the research. 4. Acknowledge those who made meaningful contributions. 5. Be ready and willing to share the data, analyses, and results. 6. Clearly identify any assumptions, limitations, or outstanding questions in the research.