1 slide aqa - business statistics, quantitative analysis peter matthews [email protected] fda...
TRANSCRIPT
2 Slide
LECTURE
The aim today is to describe
What Are Statistics
Where are they used
3 Slide
What is StatisticsI need help! Applications in Business
• and Economics
Statistics is the science of learning from data, and of measuring, controlling, and communicating uncertainty Plus : - it’s a pain and lots of people hate it.
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Application Areas of Statistics
Accounting
• Auditing
• Costing
Finance
• Financial trends
• Forecasting
Management
• Describe employees
• Quality improvement
Marketing
• Consumer preferences
• Marketing mix effects
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Applications in Business and Economics
Accounting
Economics
Public accounting firms use statisticalsampling procedures when conductingaudits for their clients.
Economists use statistical informationin making forecasts about the future ofthe economy or some aspect of it.
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Applications in Business and Economics
A variety of statistical quality control charts are used to monitorthe output of a production process.
Production
Electronic point-of-sale scanners atretail checkout counters are used tocollect data for a variety of marketingresearch applications.
Marketing
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Applications in Business and Economics
Financial advisers use price-earnings ratios anddividend yields to guide their investmentrecommendations.
Finance
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Why Collect Data?
Obtain input to a research study Measure performance Assist in formulating decision
alternatives Satisfy curiosity
•Knowledge for the sake of knowledge
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Data and Data Sets
The Data are the facts and figures collected, summarized, analyzed, and interpreted.
Data collected in a particular study are referred
to as the data set.
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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 data set is the number of elements multiplied by the number of variables.
Elements, Variables, and Observations
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Stock Annual Earn/Exchange Sales(£M) Share(£)
Data, Data Sets, Elements, Variables, and Observations
Company
Dataram EnergySouth Keystone LandCare Psychemedics
AMEX 73.10 0.86 OTC 74.00 1.67 NYSE 365.70 0.86 NYSE 111.40 0.33 AMEX 17.60 0.13
VariablesElement
Names
Data Set
Observation
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Data can be further classified as being qualitative or quantitative. Data can be further classified as being qualitative or quantitative.
The statistical analysis that is appropriate depends on whether the data for the variable are qualitative or quantitative.
The statistical analysis that is appropriate depends on whether the data for the variable are qualitative or quantitative.
In general, there are more alternatives for statistical analysis when the data are quantitative. In general, there are more alternatives for statistical analysis when the data are quantitative.
Qualitative and Quantitative Data
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Qualitative Data
Labels or names used to identify an attribute of each element Labels or names used to identify an attribute of each element
Often referred to as categorical data Often referred to as categorical data
Use either the nominal or ordinal scale of measurement Use either the nominal or ordinal scale of measurement
Can be either numeric or nonnumeric Can be either numeric or nonnumeric
Appropriate statistical analyses are rather limited Appropriate statistical analyses are rather limited
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Quantitative Data
Quantitative data indicate how many or how much: Quantitative data indicate how many or how much:
discrete, if measuring how many (finite) discrete, if measuring how many (finite)
continuous, if measuring how much (infinite) continuous, if measuring how much (infinite)
Quantitative data are always numeric. Quantitative data are always numeric.
Ordinary arithmetic operations are meaningful for quantitative data. Ordinary arithmetic operations are meaningful for quantitative data.
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Types of Data
Data
Numerical(Quantitative)
Categorical(Qualitative)
Discrete Continuous
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DataSources
Primary Secondary
Experiment Published(& On-Line)
Survey Observation
Data Sources
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Data Sources
Existing Sources (Secondary)
Within a firm – almost any department
Business database services – Dow Jones & Co.
Government agencies - U.S. Department of Labor
Industry associations – Travel Industry Association of America
Special-interest organizations – Graduate Management Admission Council
Internet – more and more firms
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Statistical Studies
Data Sources (Continued)
In experimental studies the variables of interestare first identified. Then one or more factors arecontrolled so that data can be obtained about howthe factors influence the variables.
In experimental studies the variables of interestare first identified. Then one or more factors arecontrolled so that data can be obtained about howthe factors influence the variables.
In observational (non-experimental) studies no attempt is made to control or influence the variables of interest.
In observational (non-experimental) studies no attempt is made to control or influence the variables of interest.
a survey is agood
example
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Data Acquisition Considerations
Time Requirement
Cost of Acquisition
Data Errors
• Searching for information can be time consuming.• Information may no longer be useful by the time it
is available.
• Organizations often charge for information even when it is not their primary business activity.
• Using any data that happens to be available or that were acquired with little care can lead to poor and misleading information.
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What Is Statistics? Collecting data
• e.g., Survey Presenting data
• e.g., Charts & tables
Characterizing data• e.g., Average
Data Analysis
Decision-Making
Why?Why?
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Descriptive Statistics
Descriptive statistics are the tabular, graphical, and numerical methods used to summarize data.
Descriptive Statistics: These are statistical
methods used to describe data that
have been collected.
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Example: Dixon Car Repair
The manager would like to have a betterunderstanding of the costof parts used in the enginetune-ups performed in theshop. She examines 50customer invoices for tune-ups. The costs
of parts,rounded to the nearest £, are listed on the
nextslide.
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91 78 93 57 75 52 99 80 97 6271 69 72 89 66 75 79 75 72 76104 74 62 68 97 105 77 65 80 10985 97 88 68 83 68 71 69 67 7462 82 98 101 79 105 79 69 62 73
Example: Hudson Auto Repair
Sample of Parts Cost for 50 Tune-ups
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Tabular Summary: Frequency and Percent Frequency
50-59 60-69 70-79 80-89 90-99 100-109
2 13 16 7 7 5 50
4 26 32 14 14 10 100
(2/50)100
Parts Cost (£)
Parts Frequency
PercentFrequency
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Graphical Summary: Histogram
2
4
6
8
10
12
14
16
18
PartsCost ($)
Fre
qu
en
cy
5059 6069 7079 8089 9099 100-110
Tune-up Parts Cost
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Inferential Statistics Involves
• Estimation
• Hypothesis testing
Purpose
• Make decisions about population characteristics
Population?Population?
Inferential Statistics: These are statistical methods used to find out something about population based on a sample.
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Statistical Inference
Population
Sample
Statistical inference
Census
Sample survey
the set of all elements of interest in a particular study
a subset of the population
the process of using data obtained from a sample to make estimates and test hypotheses about the characteristics of a population
collecting data for a population
collecting data for a sample
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Statistical Analysis Using Microsoft Excel
Statistical analysis typically involves working with large amounts of dataa. Computer software is typically used to conduct the analysis. Frequently the data that is to be analyzed resides in a spreadsheet.
Modern spreadsheet packages are capable of data management, analysis, and presentation. MS Excel is the most widely available spreadsheet software in business organizations.
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Excel Worksheet (showing data)
Note: Rows 10-51 are not shown.
Statistical Analysis Using Microsoft Excel
A B C D
1 Customer Invoice #Parts
Cost ($)Labor
Cost ($)2 Sam Abrams 20994 91 1853 Mary Gagnon 21003 71 2054 Ted Dunn 21010 104 1925 ABC Appliances 21094 85 1786 Harry Morgan 21116 62 2427 Sara Morehead 21155 78 1488 Vista Travel, Inc. 21172 69 1659 John Williams 21198 74 190
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Excel Formula Worksheet
Note: Columns A-B and rows 10-51 are not shown.
Statistical Analysis Using Microsoft Excel
C D E F G
1Parts
Cost ($)Labor
Cost ($)2 91 185 Average Parts Cost =AVERAGE(C2:C51)3 71 2054 104 1925 85 1786 62 2427 78 1488 69 1659 74 190
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Excel Value Worksheet
Note: Columns A-B and rows 10-51 are not shown.
Statistical Analysis Using Microsoft Excel
C D E F G
1Parts
Cost ($)Labor
Cost ($)2 91 185 Average Parts Cost 793 71 2054 104 1925 85 1786 62 2427 78 1488 69 1659 74 190
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