TEN WAYS TO MISLEADWITH STATISTICS

• Data Collection• Presenting Data

1-4: Data Collection

1. Shape the answers with a biased or leading question.

Don’t you think that we should stop physical contact in the NHL

so that players like Sydney Crosby don’t get concussions?

2. Shape the answers by limiting the answer options.

What’s your favourite kind of music?:

a) country b) pop c) opera

3. Confuse respondents with a vague question.

Do you think that the hat policy is really not a very good idea?

4. Skew your results with a small sample size.

Can you predict how many people like hats

with a sample size of 2

(out of a population of 50)?

5. Skew your results by selecting a biased sample.

To find out about Facebook use among GVC students, you survey your 5 friends – would the results

be accurate?

6-10: Presenting Data

6. Leave out important information

Leave the y or x axis undefined.

Do not define key terms

Keep the variables vague

“Man. named child poverty capital”Tuesday, November 24, 2009, CBC News

The Social Planning Council of Winnipeg says Manitoba is the child poverty capital of Canada once again.

In a report released Tuesday, the council stated that nearly ONE IN FIVE Manitoba children lives in poverty and more than 68% of aboriginal children under the age of six in Winnipeg live in poverty.

What info is missing?

How do they define poverty?Poverty is defined as an income of

$38,000 for a family of four.Cost of living in Manitoba is much less

than in most other provinces.People think of poverty like the starving,

naked children in Africa.

Vehicle SafetyProbability of:

SUV Minivan

Life threatening head injury

16% 2%

Life threatening chest injury

20% 4%

Life threatening leg injury

35% 1%

What info is missing?

What speed was used in the crash tests?

What are other factors involved in possible accidents?

How old are the vehicles that were tested?

What kinds of vans and SUVs were tested?

7. Skew the baseline of a bar graph.

Draw attention to small differences by manipulating the y-axis.

Start the y-axis at a number that is close to your results.

8. Use a misleading average.

Having one zero or one high mark skews what the true average is.

Eg:The average mark for the poetry assignment in Mr. G’s class is 66% based on a select sample from the class. Johnny: 81% Jimmy: 83% Jennifer: 85% Jake: 0% Jill 82%

Without the 0% the average is now 83% - a more honest reflection of how this group performed.

9. Use percentages instead of raw numbers.

Percentages tend to hide the sample size

For Example: 47% of Canadians disapprove of Stephen

Harper’s job performance – CBC News (Dec 2009).

Raw data: 141 out of 300 randomly selected Canadians (total population approx 25 million)

10. Make something out of nothing.

Draw attention to big numbers.

Eg: “My opponent wants to spend two million dollars on a new logo for Manitoba.”

Two million dollars is only .01% of Manitoba’s budget. Funding for Public Schools in 2008 was 238 million and a much higher % of the total budget.

For more info, check out ‘How to Create Misleading Statistics in 6 Easy Steps http://blog.makingitclear.com/2010/03/25/statistics/