This chapter introduces statistics and key concepts. It discusses why statistics is studied, the difference between descriptive and inferential statistics, and the different types of variables - qualitative vs. quantitative, discrete vs. continuous. It also covers levels of measurement - nominal, ordinal, interval, and ratio scales. The goals are to understand why we study statistics and distinguish between these fundamental statistical concepts.

1. 1-1
Chapter
One
McGraw-Hill/Irwin © 2005 The McGraw-Hill Companies, Inc., All Rights Reserved.

2. 1-2
Chapter One
What is Statistics?
GOALS
When you have completed this chapter, you will be able to:
ONE
Understand why we study statistics.
TWO
Explain what is meant by descriptive statistics and inferential statistics.
THREE
Distinguish between a qualitative variable and a quantitative variable.
FOUR
Distinguish between a discrete variable and a continuous variable.
FIVE
Distinguish among the nominal, ordinal, interval, and ratio levels
of measurement.
SIX
Define the terms mutually exclusive and exhaustive. Goals

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Statistics is the science
of collecting, organizing,
presenting, analyzing,
and interpreting
numerical data to assist
in making more
effective decisions.
µ Σ β
λ σ
What is Meant by Statistics?

4. 1-4
Statistical techniques are
used extensively by
marketing, accounting,
quality control,
consumers, professional
sports people, hospital
administrators,
educators, politicians,
physicians, and many
others.
Who Uses Statistics?

5. 1-5
Descriptive Statistics: Methods of organizing,
summarizing, and presenting data in an informative way.
EXAMPLE 1: A EXAMPLE 2: According
Gallup poll found that to Consumer Reports,
49% of the people in a General Electric washing
survey knew the name machine owners reported
of the first book of the 9 problems per 100
Bible. The statistic 49 machines during 2001.
describes the number The statistic 9 describes
out of every 100 the number of problems
persons who knew the out of every 100 machines.
answer.
Types of Statistics

6. 1-6
Inferential Statistics: A decision, estimate,
prediction, or generalization about a population,
based on a sample.
A Population A Sample is a
is a Collection portion, or part,
of all possible of the population
individuals, of interest
objects, or
measurements of
interest.
Types of Statistics

7. 1-7
Example 1: TV Example 2: Wine
networks constantly tasters sip a few drops
monitor the of wine to make a
popularity of their decision with respect
programs by hiring to all the wine waiting
Nielsen and other to be released for sale.
organizations to
sample the Example 3: The accounting
preferences of TV department of a large firm will
viewers. select a sample of the invoices to
check for accuracy for all the
invoices of the company.
#1
Types of Statistics
(examples of inferential statistics)

8. 1-8
For a Qualitative or Attribute Variable the
characteristic being studied is nonnumeric.
G en der
E ye
C o lo r
S ta te of
T ype of car B irt h
Types of Variables

9. 1-9
In a Quantitative Variable information is
reported numerically.
Balance in your checking account
Minutes remaining in class
Number of children in a family
Types of Variables

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Quantitative variables can be classified as either
Discrete or Continuous.
Discrete Variables: can only assume
certain values and there are usually “gaps”
between values.
Example: the number of
bedrooms in a house, or
the number of hammers
sold at the local Home
Depot (1,2,3,…,etc).
Types of Variables

11. 1-11
A Continuous Variable can assume
any value within a specified range.
The pressure in a tire
The weight of a pork chop
The height of students in a class.
Types of Variables

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D ATA
Q u a lit a t iv e o r a t t r ib u t e Q u a n t i t a t i v e o r n u m e r ic a l
(ty p e o f c a r o w n e d )
d is c r e t e c o n t in u o u s
( n u m b e r o f c h ild r e n ) ( t im e t a k e n fo r a n e x a m )
Summary of Types of Variables

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There are four levels of
data
Nominal
Ordinal
Interval
Ratio
Levels of Measurement

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Nominal level G en der
Data that is
classified into
categories and
cannot be arranged E ye
in any particular C o lo r
order.
Nominal data

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Nominal level variables must be:
Mutually exclusive
An individual, object, or
measurement is included in only
one category.
Exhaustive
Each individual, object, or
measurement must appear in one
of the categories.
Levels of Measurement

16. 1-16
Ordinal level: involves data arranged in some
order, but the differences between data values cannot
be determined or are meaningless.
During a taste test
of 4 soft drinks, 4
2
Coca Cola was
ranked number 1,
Dr. Pepper number 3
2, Pepsi number 3,
1
and Root Beer
number 4.
Levels of Measurement

17. 1-17
Interval level
Similar to the ordinal level, with the additional
property that meaningful amounts of differences
between data values can be determined. There is no
natural zero point.
Temperature on
the Fahrenheit
scale.
Levels of Measurement

18. 1-18
Ratio level: the interval level with an inherent
zero starting point. Differences and ratios are
meaningful for this level of measurement.
M ile s t ra v e le d b y s a le s M o n t h ly in c o m e
re p re s e n t a t iv e in a m o n t h
o f su rg eo n s
Levels of Measurement