The Need for Statistics

• 8-1 Why do we need statistics in psychology and in everyday life?

For psychologists using descriptive, correlational, experimental, and other research designs, statistics are the tools that allow them to measure variables and then interpret results. Yet, accurate statistical understanding benefits everyone. To be an educated person today is to be able to apply simple statistical principles to everyday reasoning. We don’t need to memorize complicated formulas to think more clearly and critically about data.

Off-the-top-of-the-head estimates often misread reality and mislead the public. Someone throws out a big, round number. Others echo it, and before long the big, round number becomes public misinformation. Two examples:

• Ten percent of people are gay or lesbian. Or is it 3 to 4 percent, as suggested by various national surveys (Module 53)?
• We ordinarily use only 10 percent of our brain. Or is it closer to 100 percent (Module 12)?

The point to remember: Doubt big, round, undocumented numbers. If you read that there are one million missing children, two million homeless, or three million spouse abusers, you can be pretty sure that someone is guessing. If they want to emphasize the problem, they will be motivated to guess big. If they want to minimize the problem, they will guess small.

FYI

When setting goals, we love big, round numbers. We’re far more likely to want to lose 20 pounds than 19 or 21 pounds. And by modifying their behavior, batters are nearly four times more likely to finish the season with a .300 average than with a .299 average (Pope & Simonsohn, 2011).

Statistical illiteracy also feeds needless health scares (Gigerenzer, 2010). In the 1990s, the British press reported a study showing that women taking a particular contraceptive pill had a 100 percent increased risk of blood clots that could produce strokes. This caused thousands of women to stop taking the pill, leading to a wave of unwanted pregnancies and an estimated 13,000 additional abortions (which also are associated with increased blood-clot risk). And what did the study actually find? A 100 percent increased risk, indeed—but only from 1 in 7000 to 2 in 7000. Such false alarms underscore the need to teach statistical reasoning and to present statistical information more transparently.