Business Statistics, 4e, by Ken Black. © 2003 John Wiley & Sons. 1-1
Business Statistics, 4th
by Ken Black
Chapter 1
Intro...
Business Statistics, 4e, by Ken Black. © 2003 25-
Learning Objectives
• Define statistics
• Become aware of a wide range o...
Business Statistics, 4e, by Ken Black. © 2003 35-
Statistics in Business
• Give specific examples of data that might
be ga...
Business Statistics, 4e, by Ken Black. © 2003 45-
Statistics in Business
• Accounting — auditing and cost estimation
• Eco...
Business Statistics, 4e, by Ken Black. © 2003 55-
What is Statistics?
• Science of gathering, analyzing,
interpreting, and...
Business Statistics, 4e, by Ken Black. © 2003 65-
Prof. Horace has defined Statistics as
follows:-
• “By statistics we mea...
Business Statistics, 4e, by Ken Black. © 2003 75-
Population Versus Sample
• Population — the whole
– a collection of pers...
Business Statistics, 4e, by Ken Black. © 2003 85-
Population
Business Statistics, 4e, by Ken Black. © 2003 95-
Population and Census Data
Identifier Color MPG
RD1 Red 12
RD2 Red 10
RD...
Business Statistics, 4e, by Ken Black. © 2003 105-
Sample and Sample Data
Identifier Color MPG
RD2 Red 10
RD5 Red 13
GR1 G...
Business Statistics, 4e, by Ken Black. © 2003 115-
Descriptive vs. Inferential Statistics
• Descriptive Statistics — using...
Business Statistics, 4e, by Ken Black. © 2003 125-
Parameter vs. Statistic
• Parameter — descriptive measure of the
popula...
Business Statistics, 4e, by Ken Black. © 2003 135-
Symbols for Population Parameters
µdenotes populationparameter
2
σ deno...
Business Statistics, 4e, by Ken Black. © 2003 145-
Symbols for Sample Statistics
x denotes sample mean
2
S denotes sample ...
Business Statistics, 4e, by Ken Black. © 2003 155-
Process of Inferential Statistics
Population
(parameter)
µ
Sample
x
(st...
Business Statistics, 4e, by Ken Black. © 2003 165-
Levels of Data Measurement
• Nominal — Lowest level of measurement
• Or...
Business Statistics, 4e, by Ken Black. © 2003 175-
Nominal Level Data
• Numbers are used to classify or categorize
Example...
Business Statistics, 4e, by Ken Black. © 2003 185-
Ordinal Level Data
• Numbers are used to indicate rank or order
– Relat...
Business Statistics, 4e, by Ken Black. © 2003 195-
Example of Ordinal Measurement
f
i
n
i
s
h
1
2
3
4
5
6
Business Statistics, 4e, by Ken Black. © 2003 205-
Ordinal Data
Faculty and staff should receive preferential
treatment fo...
Business Statistics, 4e, by Ken Black. © 2003 215-
Interval Level Data
• Distances between consecutive integers are
equal
...
Business Statistics, 4e, by Ken Black. © 2003 225-
Ratio Level Data
• Highest level of measurement
– Relative magnitude of...
Business Statistics, 4e, by Ken Black. © 2003 235-
Usage Potential of Various
Levels of Data
Nominal
Ordinal
Interval
Ratio
Business Statistics, 4e, by Ken Black. © 2003 245-
Data Level, Operations,
and Statistical Methods
Data Level
Nominal
Ordi...
Business Statistics, 4e, by Ken Black. © 2003 255-
Limitations of statistics :-
• Statistics does not study qualitative
ph...
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Ch01+of+stats

  1. 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. 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
  3. 3. Business Statistics, 4e, by Ken Black. © 2003 35- 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
  4. 4. Business Statistics, 4e, by Ken Black. © 2003 45- 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
  5. 5. Business Statistics, 4e, by Ken Black. © 2003 55- 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
  6. 6. Business Statistics, 4e, by Ken Black. © 2003 65- 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
  7. 7. Business Statistics, 4e, by Ken Black. © 2003 75- 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
  8. 8. Business Statistics, 4e, by Ken Black. © 2003 85- Population
  9. 9. Business Statistics, 4e, by Ken Black. © 2003 95- 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
  10. 10. Business Statistics, 4e, by Ken Black. © 2003 105- Sample and Sample Data Identifier Color MPG RD2 Red 10 RD5 Red 13 GR1 Green 35 GY2 Gray 18
  11. 11. Business Statistics, 4e, by Ken Black. © 2003 115- 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
  12. 12. Business Statistics, 4e, by Ken Black. © 2003 125- 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
  13. 13. Business Statistics, 4e, by Ken Black. © 2003 135- Symbols for Population Parameters µdenotes populationparameter 2 σ denotes population variance σ denotes population standard deviation
  14. 14. Business Statistics, 4e, by Ken Black. © 2003 145- Symbols for Sample Statistics x denotes sample mean 2 S denotes sample variance S denotes sample standard deviation
  15. 15. Business Statistics, 4e, by Ken Black. © 2003 155- Process of Inferential Statistics Population (parameter) µ Sample x (statistic) Calculate x to estimate µ Select a random sample
  16. 16. Business Statistics, 4e, by Ken Black. © 2003 165- Levels of Data Measurement • Nominal — Lowest level of measurement • Ordinal • Interval • Ratio — Highest level of measurement
  17. 17. Business Statistics, 4e, by Ken Black. © 2003 175- 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
  18. 18. Business Statistics, 4e, by Ken Black. © 2003 185- 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
  19. 19. Business Statistics, 4e, by Ken Black. © 2003 195- Example of Ordinal Measurement f i n i s h 1 2 3 4 5 6
  20. 20. Business Statistics, 4e, by Ken Black. © 2003 205- Ordinal Data Faculty and staff should receive preferential treatment for parking space. 1 2 3 4 5 Strongly Agree Agree Strongly Disagree DisagreeNeutral
  21. 21. Business Statistics, 4e, by Ken Black. © 2003 215- 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
  22. 22. Business Statistics, 4e, by Ken Black. © 2003 225- 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.
  23. 23. Business Statistics, 4e, by Ken Black. © 2003 235- Usage Potential of Various Levels of Data Nominal Ordinal Interval Ratio
  24. 24. Business Statistics, 4e, by Ken Black. © 2003 245- 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
  25. 25. Business Statistics, 4e, by Ken Black. © 2003 255- 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

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