I recently started reading Richard Muller's book, *Physics for Future Presidents*, and it made wonder what statisticians would include in a book of statistics for future presidents. Please let me know your thoughts in the comments space of this blog entry or by emailing me: pierson@amstat.org.

I'm aware of lists for the most important statistical skills for statisticians (e.g., The 5 Most Critical Statistical Concepts), K-12 students, non-science majors, and professions such as journalists (e.g., News and Numbers by Victor Cohn) and clinicians. I'm eager to hear what statistics you’d recommend for future presidents (or policymakers more generally) and how it would compare with the recommended statistical skills/concepts for others.

Muller's book organizes his book into a discussion of five topics: terrorism; energy; nuclear weapons, power and waste; space; and global warming. Would a Statistics-for-Future-Presidents book also be organized by such topic areas or would be organized into more statistical thinking categories (interpreting data, assessing study/report conclusions and survey results, decisionmaking in presence of uncertainty, assessing/managing risk, …) or some combination of these?

I'm aware of lists for the most important statistical skills for statisticians (e.g., The 5 Most Critical Statistical Concepts), K-12 students, non-science majors, and professions such as journalists (e.g., News and Numbers by Victor Cohn) and clinicians. I'm eager to hear what statistics you’d recommend for future presidents (or policymakers more generally) and how it would compare with the recommended statistical skills/concepts for others.

Muller's book organizes his book into a discussion of five topics: terrorism; energy; nuclear weapons, power and waste; space; and global warming. Would a Statistics-for-Future-Presidents book also be organized by such topic areas or would be organized into more statistical thinking categories (interpreting data, assessing study/report conclusions and survey results, decisionmaking in presence of uncertainty, assessing/managing risk, …) or some combination of these?

7 comments

112 views

Some of the other suggestions are good for policy wonks behind the scenes, or for bureaucrats, but I think the first idea would have the most widespread audience.

At the end of the course you should be able to…

- Apply basic statistical methods

- Recognize more advanced statistical techniques

- Distinguish good statistical practice from bad

- Know when to call in statistical experts

1. Decision-making under uncertainty, e.g. decision trees (the OR kind, not the machine learning kind)

2. Bayesian approaches to environmental decisions

3. The hazards of drawing conclusions from observational data (Stan Young's article in Significance, Sept. 2011)

Peter Bruce, statistics.com

-- the importance of question wording and context, study design for causal claims and survey statistics

-- distinguishing pattern from random chance (importance of measures of uncertainty)

-- decision making in the presence of uncertainty (decision theory ideas, probabilistic considerations of risk)

-- how wise statistical analysis informs debate (basically, fight the perception of lies, damn lies,and statistics)

-- maybe a chapter on what statisticians can do beyond the intro stat level.

Jerry Reiter

Duke University

For example, let them know why random and mandatory surveys are essential to getting good information. Here's a Representative bashing the ACS, from the NY Times article linked above: "'We’re spending $70 per person to fill this out. That’s just not cost effective,' [Webster] continued, 'especially since in the end this is not a scientific survey. It’s a random survey.'"