soodoku/Journalists and Numbers

## Journalists and Numbers
Some things journalists may want to consider:

1. Anecdotes can mislead. People seeing another yet another episodic story on crime may infer that crime is increasing.
   So report numbers where trustworthy numerical data are available.

2. But numbers need to be reported carefully. Most people, when reading news, do not do back of the envelope calculations to interpret data correctly.
  So ill-reported numbers can mislead.

3. Rules for numbers:
  a. % changes than changes in %. The former is more impressive when the base rate is low. Latter generally a better way to report things. If confused, report t1 and t2.
  b. Reporting X things happen every 24 hours doesn't give the appropriate context. Raw frequencies rarely do. Adjusting for size of population is often times the way to go. Same for financial numbers.
  c. Summarizing studies as Study X shows A causes B can mislead. Let us assume that the study shows a causal relationship (many studies are merely correlational). But often times, there is a tiny beta. So rather than make categorical judgments, make quantitative judgment, moving A up by this much causes B to change by that much.
  d. Where possible don't say - there is a possibility of X. Everything is possible, no? However bizarre. Where probability judgments are available, report those.
	Some things journalists may want to consider:

	1. Anecdotes can mislead. People seeing another yet another episodic story on crime may infer that crime is increasing.
	So report numbers where trustworthy numerical data are available.

	2. But numbers need to be reported carefully. Most people, when reading news, do not do back of the envelope calculations to interpret data correctly.
	So ill-reported numbers can mislead.

	3. Rules for numbers:
	a. % changes than changes in %. The former is more impressive when the base rate is low. Latter generally a better way to report things. If confused, report t1 and t2.
	b. Reporting X things happen every 24 hours doesn't give the appropriate context. Raw frequencies rarely do. Adjusting for size of population is often times the way to go. Same for financial numbers.
	c. Summarizing studies as Study X shows A causes B can mislead. Let us assume that the study shows a causal relationship (many studies are merely correlational). But often times, there is a tiny beta. So rather than make categorical judgments, make quantitative judgment, moving A up by this much causes B to change by that much.
	d. Where possible don't say - there is a possibility of X. Everything is possible, no? However bizarre. Where probability judgments are available, report those.