Page 67 - Statistics for Dummies

Chapter 4: Tools of the Trade
Bias
Bias is a word you hear all the time, and you probably know that it means
something bad. But what really constitutes bias? Bias is systematic favoritism
that is present in the data collection process, resulting in lopsided, mislead-
ing results. Bias can occur in any of a number of ways:
✓ In the way the sample is selected: For example, if you want to estimate
how much holiday shopping people in the United States plan to do this
year, and you take your clipboard and head out to a shopping mall on the
day after Thanksgiving to ask customers about their shopping plans, you
have bias in your sampling process. Your sample tends to favor those
die-hard shoppers at that particular mall who were braving the massive
crowds on that day known to retailers and shoppers as “Black Friday.”
✓ In the way data are collected: Poll questions are a major source of bias.
Because researchers are often looking for a particular result, the ques-
tions they ask can often reflect and lead to that expected result. For 51
example, the issue of a tax levy to help support local schools is some-
thing every voter faces at one time or another. A poll question asking,
“Don’t you think it would be a great investment in our future to support
the local schools?” has a bit of bias. On the other hand, so does “Aren’t
you tired of paying money out of your pocket to educate other people’s
children?” Question wording can have a huge impact on results.
Other issues that result in bias with polls are timing, length, level of ques-
tion difficulty, and the manner in which the individuals in the sample were
contacted (phone, mail, house-to-house, and so on). See Chapter 16 for more
information on designing and evaluating polls and surveys.
When examining polling results that are important to you or that you’re partic-
ularly interested in, find out what questions were asked and exactly how the
questions were worded before drawing your conclusions about the results.
Mean (Average)
The mean, also referred to by statisticians as the average, is the most
common statistic used to measure the center, or middle, of a numerical data
set. The mean is the sum of all the numbers divided by the total number of
numbers. The mean of the entire population is called the population mean,
and the mean of a sample is called the sample mean. (See Chapter 5 for more
on the mean.)

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