Page 31 - Statistics for Dummies

Chapter 1: Statistics in a Nutshell
✓ Numerical data represent measurements or counts, where the actual
numbers have meaning (such as height and weight). With numerical
data, more features can be summarized besides the number or percent-
age in each group. Some of these features include
• Measures of center (in other words, where is the “middle” of the

data?)

• Measures of spread (how diverse or how concentrated are the
data around the center?)

• If appropriate, numbers that measure the relationship between
two variables (such as height and weight)
Some descriptive statistics are more appropriate than others in certain situa-
tions; for example, the average isn’t always the best measure of the center of a
data set; the median is often a better choice. And the standard deviation isn’t
the only measure of variability on the block; the interquartile range has excel-
lent qualities too. You need to be able to discern, interpret, and evaluate the
types of descriptive statistics being presented to you on a daily basis and to 15
know when a more appropriate statistic is in order.
The descriptive statistics you see most often are calculated, interpreted,
compared, and evaluated in Chapter 5. These commonly used descriptive
statistics include frequencies and relative frequencies (counts and percents)
for categorical data; and the mean, median, standard deviation, percentiles,
and their combinations for numerical data.
Charts and graphs
Data is summarized in a visual way using charts and/or graphs. These are
displays that are organized to give you a big picture of the data in a flash
and/or to zoom in on a particular result that was found. In this world of quick
information and mini-sound bites, graphs and charts are commonplace. Most
graphs and charts make their points clearly, effectively, and fairly; however,
they can leave room for too much poetic license, and as a result, can expose
you to a high number of misleading and incorrect graphs and charts.
In Chapters 6 and 7, I cover the major types of graphs and charts used to
summarize both categorical and numerical data (see the preceding section
for more about these types of data). You see how to make them, what their
purposes are, and how to interpret the results. I also show you lots of ways
that graphs and charts can be made to be misleading and how you can quickly
spot the problems. It’s a matter of being able to say “Wait a minute here!
That’s not right!” and knowing why not. Here are some highlights:

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