1
Stat240. Describing Data by Tables and Graphs.
(Chapter 2, sects 1, 2, 3).
Handout 2
some good
Stats Links:
http://www.learner.org/exhibits/statistics/
Gallup
 http://www.gallup.com/
 the famous
polling company
Some Terminology
•
Variable
: a characteristic which varies over time or in
different individuals/objects.
– Response of a student. (Age, height, religious affiliation, social
class).
•
Population
: the whole set of units on which some feature is
investigated.
– American registered voters. The set of students.
•
Sample
: a subset of the population.
– In the poll example, the set of students who were interviewed.
•
Sample/experimental unit
: the unit on which
measurements are taken.
– The individuals selected to be interviewed.
– The individuals selected for an experiment.
•
Sample size
: the number of sample/experimental units.
•A
measurement
results when a variable is actually
measured on an experimental unit. A set of measurements
is called
data.
Example 2.1
Student
GPA
Gender
Year
Major
Units Enrolled
1
2 F
Fr
Psychology
16
2
2.3 F
So
Maths
15
3
2.9 M
So
English
17
4
2.7 M
Fr
English
15
52
.
6
F
J
r
B
u
s
i
n
e
s
s
1
4
A sample of n = 500 students was selected from all undergraduates at
a large university to investigate gender and major distribution
How many variables have you measured?
Univariate data:
One variable is measured on a single experimental unit.
Bivariate data:
Two variables are measured on a single experimental unit.
Multivariate data:
More than two variables are measured on a single
experimental unit.
Types of variables and
information
•
Qualitative variables
(categorical data)
measure a quality or characteristic on each
experimental unit .
Examples:
• Make of car (Dodge, Honda, Ford…)
• Gender (male, female)
• Hair color (black, brown, blonde…)
• State of birth (California, Arizona,….)
• Data: frequency, that is the number of times a
particular category is observed in the
sample/population.
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•
Quantitative variables (numerical )
measure a
numerical quantity on each experimental unit.
9
Discrete 
if it can assume only a finite or
countable number of values.
9
Continuous 
if it can assume the infinitely
many values corresponding to the points on a
line interval.
– Data: are the actual measurements.
– Example:
• For a particular day, the number of cars entering a college
campus is measured. (
Quantitative discrete)
• Time until a light bulb burns out (
Quantitative
continuous)
categorical
Example 2.1 cont’d
Student
GPA
Gender
Year
Major
Units Enrolled
1
2 F
Fr
Psychology
16
2
2.3 F
So
Maths
15
32
.
9
M
S
oE
n
g
l
i
s
h
1
7
42
.
7
M
F
r
E
n
g
l
i
s
h
1
5
5
2.6 F
Jr
Business
14
Sample
units
numerical
numerical
Sample size: n=500
Types of Variables
variables
Qualitative
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 Spring '08
 Jeneralczuk
 Statistics, Frequency distribution, Bar chart, Histogram

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