1. Business Statistics, 4e, by Ken Black. © 2003 John Wiley & Sons. 1-1
Business Statistics, 4th
by Ken Black
Chapter 1
Introduction
to Statistics
Discrete Distributions

2. Business Statistics, 4e, by Ken Black. © 2003 25-
Learning Objectives
• Define statistics
• Become aware of a wide range of
applications of statistics in business
• Differentiate between descriptive and
inferential statistics
• Classify numbers by level of data and
understand why doing so is important

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Statistics in Business
• Give specific examples of data that might
be gathered from each of the following
business disciplines and the industry.
• Functional Areas :- Accounting, Finance,
Production, Marketing,
• Industry :- Manufacturing, Agriculture,
Insurance, Banking, Travel, Healthcare

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Statistics in Business
• Accounting — auditing and cost estimation
• Economics — regional, national, and international
economic performance
• Finance — investments and portfolio management
• Management — human resources, compensation, and
quality management
• Management Information Systems — performance of
systems which gather, summarize, and disseminate
information to various managerial levels
• Marketing — market analysis and consumer research
• International Business — market and demographic
analysis

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What is Statistics?
• Science of gathering, analyzing,
interpreting, and presenting data
• Branch of mathematics
• Course of study
• Facts and figures
• A death
• Measurement taken on a sample
• Type of distribution being used to analyze
data

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Prof. Horace has defined Statistics as
follows:-
• “By statistics we mean aggregate of facts affected to a
marked extent by multiplicity of causes, numerically
expressed, enumerated or estimated according to
reasonable standards of accuracy, collected in a systematic
manner for a predetermined purpose and placed in relation
to each other.”Therefore:-
• Statistics are aggregate of facts
• Statistics are affected to a marked extent by multiplicity of
causes
• Statistics are numerically expressed
• Statistics are enumerated or estimated according to
reasonable standards of accuracy
• Statistics are collected in a systematic manner
• Statistics are collected for a predetermined purpose
• Statistics should be placed in relation to each other

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Population Versus Sample
• Population — the whole
– a collection of persons, objects, or items under
study
• Census — gathering data from the entire
population
• Sample — a portion of the whole
– a subset of the population

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Population

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Population and Census Data
Identifier Color MPG
RD1 Red 12
RD2 Red 10
RD3 Red 13
RD4 Red 10
RD5 Red 13
BL1 Blue 27
BL2 Blue 24
GR1 Green 35
GR2 Green 35
GY1 Gray 15
GY2 Gray 18
GY3 Gray 17

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Sample and Sample Data
Identifier Color MPG
RD2 Red 10
RD5 Red 13
GR1 Green 35
GY2 Gray 18

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Descriptive vs. Inferential Statistics
• Descriptive Statistics — using data gathered
on a group to describe or reach conclusions
about that same group only
• Inferential Statistics — using sample data to
reach conclusions about the population
from which the sample was taken

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Parameter vs. Statistic
• Parameter — descriptive measure of the
population
– Usually represented by Greek letters
• Statistic — descriptive measure of a sample
– Usually represented by Roman letters

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Symbols for Population Parameters
µdenotes populationparameter
2
σ denotes population variance
σ denotes population standard deviation

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Symbols for Sample Statistics
x denotes sample mean
2
S denotes sample variance
S denotes sample standard deviation

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Process of Inferential Statistics
Population
(parameter)
µ
Sample
x
(statistic)
Calculate x
to estimate µ
Select a
random sample

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Levels of Data Measurement
• Nominal — Lowest level of measurement
• Ordinal
• Interval
• Ratio — Highest level of measurement

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Nominal Level Data
• Numbers are used to classify or categorize
Example: Employment Classification
– 1 for Educator
– 2 for Construction Worker
– 3 for Manufacturing Worker
Example: Ethnicity
– 1 for African-American
– 2 for Anglo-American
– 3 for Hispanic-American

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Ordinal Level Data
• Numbers are used to indicate rank or order
– Relative magnitude of numbers is meaningful
– Differences between numbers are not comparable
Example: Ranking productivity of employees
Example: Taste test ranking of three brands of soft drink
Example: Position within an organization
– 1 for President
– 2 for Vice President
– 3 for Plant Manager
– 4 for Department Supervisor
– 5 for Employee

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Example of Ordinal Measurement
f
i
n
i
s
h
1
2
3
4
5
6

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Ordinal Data
Faculty and staff should receive preferential
treatment for parking space.
1 2 3 4 5
Strongly
Agree
Agree Strongly
Disagree
DisagreeNeutral

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Interval Level Data
• Distances between consecutive integers are
equal
– Relative magnitude of numbers is meaningful
– Differences between numbers are comparable
– Location of origin, zero, is arbitrary
– Vertical intercept of unit of measure transform
function is not zero
Example: Fahrenheit Temperature
Example: Calendar Time
Example: Monetary Utility

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Ratio Level Data
• Highest level of measurement
– Relative magnitude of numbers is meaningful
– Differences between numbers are comparable
– Location of origin, zero, is absolute (natural)
– Vertical intercept of unit of measure transform
function is zero
Examples: Height, Weight, and Volume
Example: Monetary Variables, such as Profit and
Loss, Revenues, and Expenses
Example: Financial ratios, such as P/E Ratio,
Inventory Turnover, and Quick Ratio.

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Usage Potential of Various
Levels of Data
Nominal
Ordinal
Interval
Ratio

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Data Level, Operations,
and Statistical Methods
Data Level
Nominal
Ordinal
Interval
Ratio
Meaningful Operations
Classifying and Counting
All of the above plus Ranking
All of the above plus Addition,
Subtraction, Multiplication, and
Division
All of the above
Statistical
Methods
Nonparametric
Nonparametric
Parametric
Parametric

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Limitations of statistics :-
• Statistics does not study qualitative
phenomenon
• Statistics does not study individuals
• Statistical data is only approximately and
not mathematically correct
• Statistics is only one of the methods of
studying a problem
• Statistics can be misused