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AQA - Business Statistics , Quantitative Analysis

Peter Matthewsmatthewsp@bpc.ac.uk

FDA B&M 2011-12

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LECTURE

The aim today is to describe

What Are Statistics

Where are they used

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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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