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which has undergone no additional research to prove the claim Do you know why you're paying
$720 for car insurance every six months, while you're roommate is paying only $450 If a
mammogram comes back positive for breast cancer, is there any chance that this is a false
positive Should you be surprised that no ethnic applicants were hired to a company if three
applicants were to be selected, when 15 were Caucasian and 5 were Hispanic Is there a reason
to suspect inequality It should not surprise you that these can be answered with probability and
statistics.
1.1.2 Types of Data
In order to be able to reach the goals mentioned above, we need to have some sort of information
about which to make our decisions – we call this information data.
Data comes in two main categories: quantitative and qualitative/categorical.
Quantitative variables, as the title implies, deal with numerical quantities. For example, the
average revenue of a Whole Foods market store is considered a quantitative variable, since the
measurement is a number.
Qualitative variables, on the other hand, deal with qualities. For example, the type of television
that a customer is likely to purchase is considered a qualitative variable, since its value will be,
for instance, plasma, LED, LCD, etc.
1.1.3 Not All Quantitative Variables Are As They Appear!
Just because a variable is stated as a numerical value doesn‟t mean that it can be treated as a
numerical value. A variable must be classified according to its scale of measurement.
For instance, suppose you are to test three marketing tactics on customers. You call these tactics,
Tactics 1, 2, and 3, respectively. These tactics have numerical values, but the numbers do not
have any ordering significance. That is, tactic 1 is not necessarily better than tactic 3. These
numbers serve simply as names for the values of the variables and cannot be numerically
compared. We call this a variable of nominal scale.
Suppose that a business magazine reports the top three new businesses in the city each month.
That is, we have businesses 1, 2, and 3, where 1 is considered the best of the three, 2 the second
best, and 3 the third best. In this case, we can talk about 1 being better than 2 and 3 and 3 being
worse than 1 and 2. This type of variable has the properties of a nominal scaled variable, but also
has the property of order. We call this a variable of ordinal scale.
In another example, consider the variable IQ. Suppose two people have IQ‟s of 100 and 120.
Based on this information, we can say that the person with 120 has a higher IQ. However, we
can also say that the second person has an IQ that is 20 points higher than the first person. We
couldn‟t really say this for the example above. In addition to being nominal (a person can be
identified by their value) and ordinal (can rank the scores), we can also talk about the differences
in scores. This type of variable is of interval scale.
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