Business Statistics
Instructor: Ya Ding
• Associate Professor at Department of Economics
and Finance
• Office:
• Email:
SME building C511
dingya@uestc.edu.cn
Teaching Assistant:
• Office:
• Email:
1
Business Statistics
Textbook:
Statistics for Business and Economics, by
Anderson, Sweeney and Williams, 11th edtion
2
Business Statistics
Grading:
Final Exam (60%)
Group Assignments (20%)
In-class Quizzes (20%)
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CHAPTER 1
DATA AND STATISTICS
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Learning Objectives
Define Statistics
I need
help!
Applications of Statistics in
Business and Economics
Understand Basic Concepts
of Data
Differentiate between
Descriptive Statistics and
Statistical Inference
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“The sign of a truly educated
person is to be deeply moved
by statistics.”
— George Bernard Shaw
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What is Statistics
Statistics is used in our daily life
Chengdu Average Monthly Temperature
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What is Statistics
Statistics – numerical facts such as averages,
medians, percents, and index numbers that
help us understand a variety of business and
economic conditions
Statistics – the art and science of collecting,
analyzing, presenting, and interpreting data
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Applications in
Business and Economics
Accounting
Economics
Marketing
Production
◼ Finance
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Data and Data Sets
Data are the facts and figures collected, summarized,
analyzed, and interpreted.
◼ The data collected in a particular study are referred
to as the data set.
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Elements, Variables, and Observations
◼ The elements are the entities on which data are
collected.
◼ A variable is a characteristic of interest for the elements.
◼ The set of measurements collected for a particular
element is called an observation.
◼ The total number of data values in a complete data
set is the number of elements multiplied by the
number of variables.
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Data, Data Sets,
Elements, Variables, and Observations
Variables
Element
Names
Company
Dataram
EnergySouth
Keystone
LandCare
Psychemedics
Stock
Exchange
NQ
N
N
NQ
N
Annual
Earn/
Sales($M) Share($)
73.10
74.00
365.70
111.40
17.60
0.86
1.67
0.86
0.33
0.13
Data Set
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Scales of Measurement
Data
Qualitative
Numerical
Nominal
Ordinal
Quantitative
Non-numerical
Nominal
Ordinal
Numerical
Interval
Ratio
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Cross-Sectional and Time Series Data
Cross-sectional data are collected at the same or
approximately the same point in time.
Example: Gross Domestic Product (GDP) of each
country in the world at 2014.
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Time Series Data
Time series data are collected over several time
periods.
Example: Annual GDP of China in the last ten years.
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Data Sources
Primary Data
• Raw information collected by researchers
for a specific purpose
Secondary Data
• Information obtained by studying the
reports of other researchers
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Data Acquisition Considerations
Time Requirement
•
•
Searching for information can be time consuming.
Information may no longer be useful by the time it
is available.
Cost of Acquisition
•
Organizations often charge for information even
when it is not their primary business activity.
Data Errors
• Using any data that happen to be available or were
acquired with little care can lead to misleading
information.
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Statistics in Business
Branches of statistics
• Descriptive – using data gathered on a group to
describe or reach conclusions about the group
• Inferential – data gathered from a sample and used to
reach conclusions about the population from which the
data was gathered
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Descriptive Statistics
Descriptive statistics are the tabular, graphical, and
numerical methods used to summarize and present
data.
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Example: Hudson Auto Repair
The manager of Hudson Auto
would like to have a better
understanding of the cost
of parts used in the engine
tune-ups performed in the
shop. She examines 50
customer invoices for tune-ups. The costs of parts,
rounded to the nearest dollar, are listed on the next
slide.
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Example: Hudson Auto Repair
Sample of Parts Cost ($) for 50 Tune-ups
91
71
104
85
62
78
69
74
97
82
93
72
62
88
98
57
89
68
68
101
75
66
97
83
79
52
75
105
68
105
99
79
77
71
79
80
75
65
69
69
97
72
80
67
62
62
76
109
74
73
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Tabular Summary:
Frequency and Percent Frequency
Parts
Cost ($)
50-59
60-69
70-79
80-89
90-99
100-109
Parts
Frequency
2
13
16
7
7
5
50
Percent
Frequency
4
26
(2/50)100
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14
14
10
100
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Graphical Summary: Histogram
Tune-up Parts Cost
18
16
Frequency
14
12
10
8
6
4
2
Parts
50-59 60-69 70-79 80-89 90-99 100-110 Cost ($)
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Numerical Descriptive Statistics
◼ The most common numerical descriptive statistic
is the average (or mean).
◼ Hudson’s average cost of parts, based on the 50
tune-ups studied, is $79 (found by summing the
50 cost values and then dividing by 50).
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Statistical Inference
Population
- the set of all elements of interest in a
particular study
Sample - a subset of the population
Statistical inference - the process of using data obtained
from a sample to make estimates
and test hypotheses about the
characteristics of a population
Census - collecting data for a population
Sample survey - collecting data for a sample
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Process of Statistical Inference
1. Population
consists of all tuneups. Average cost of
parts is unknown.
4. The sample average
is used to estimate the
population average.
2. A sample of 50
engine tune-ups
is examined.
3. The sample data
provide a sample
average parts cost
of $79 per tune-up.
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End of Chapter 1
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