Datasheet

12
Part I: Statistics and Excel: A Marriage Made in Heaven
group receives instruction via the new method, the other receives instruction
via traditional methods. Before and after both groups receive instruction,
the researcher measures the reading speeds of all the children in this study.
What happens next? I get to that in the upcoming section entitled “Inferential
Statistics: Testing Hypotheses.”
For now, understand that the independent variable here is Method of
Instruction. The two possible values of this variable are New and Traditional.
The dependent variable is reading speed — which we might measure in
words per minute.
In general, the idea is to try and find out if changes in the independent variable
are associated with changes in the dependent variable.
In the examples that appear throughout the book, I show you how to use Excel
to calculate various characteristics of groups of scores. Keep in mind that
each time I show you a group of scores, I’m really talking about the values of a
dependent variable.
Types of data
Data come in four kinds. When you work with a variable, the way you work
with it depends on what kind of data it is.
The first variety is called nominal data. If a number is a piece of nominal data,
it’s just a name. Its value doesn’t signify anything. A good example is the
number on an athlete’s jersey. It’s just a way of identifying the athlete and
distinguishing him or her from teammates. The number doesn’t indicate the
athlete’s level of skill.
Next comes ordinal data. Ordinal data are all about order, and numbers begin
to take on meaning over and above just being identifiers. A higher number
indicates the presence of more of a particular attribute than a lower number.
One example is Moh’s Scale. Used since 1822, it’s a scale whose values are 1
through 10. Mineralogists use this scale to rate the hardness of substances.
Diamond, rated at 10, is the hardest. Talc, rated at 1, is the softest. A sub-
stance that has a given rating can scratch any substance that has a lower
rating.
What’s missing from Moh’s Scale (and from all ordinal data) is the idea of
equal intervals and equal differences. The difference between a hardness of
10 and a hardness of 8 is not the same as the difference between a hardness
of 6 and a hardness of 4.
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