Chapter 1 & Section 2.1
Exploring Data
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Typology: Summaries
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Chapter 1 & Section 2.
Exploring Data
Introduction
● Statistics:
●the science of data. We begin our study of
statistics by mastering the art of examining data.
Any set of data contains information about some
group of individuals. The information is organized
in variables.
● Individuals:
●The objects described by a set of data.
Individuals may be people, but they may also be
other things.
● Variable:
●Any characteristic of an individual.
●Can take different values for different individuals.
● A. The individuals are the BMW 318I, the
Buick Century, and the Chevrolet Blazer.
● B. The variables given are
●Vehicle type (categorical)
●Transmission type (categorical)
●Number of cylinders (quantitative)
●City MPG (quantitative)
●Highway MPG (quantitative)
Shape
● Concentrate on main features.
●Major peaks, outliers (not just the smallest and
largest observations), rough symmetry or clear
skewness.
● Types of Shapes:
Symmetr
ic
Skewed
right
Skewed
left
How to make a bar graph.
No, a pie chart is used to display one variable
with all of its categories totaling 100%
How to make a dotplot
Highway mpg for some 2000 midsize cars
Frequen cy or Count
MPG
21 22 23 24 25 26 27 28 29 30 31 32
2
4
6
8
10
How to make and read a stemplot
● With the following data, make a stemplot.
Stems (^) Leaves
How to make and read a stemplot
● Lets use the same stemplot but now split the stems
Stems (^) Leaves
Split stems
Leaves, first stem uses number 0-4, second uses numbers 5-
Divide range into equal widths and count
0 < CEO Salary < 100
100 < CEO Salary < 200
200 < CEO Salary < 300
300 < CEO Salary < 400
400 < CEO Salary < 500
500 < CEO Salary < 600
600 < CEO Salary < 700
700 < CEO Salary < 800
800 < CEO Salary < 900
Scale
Counts
New terms used when graphing data.
● Relative frequency:
●Category count divided by the total count
●Gives a percentage
● Cumulative frequency:
●Sum of category counts up to an including the
current category
● Ogives (pronounced O-Jive)
●Cumulative frequencies divided by the total count
●Relative cumulative frequency graph
● Percentile:
●The p
th
percentile of a distribution is the value such
that p percent of the observations fall at or below it.
Lets look at a table to see what an ogive
would refer to.