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Applied Statistics in Applied Statistics in Business & EconomicsBusiness & Economics

22ndnd edition edition David P. Doane and Lori E. SewardDavid P. Doane and Lori E. Seward

McGraw-Hill/Irwin Copyright © 2009 by The McGraw-Hill Companies, Inc. All rights reserved.

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Overview of StatisticsOverview of Statistics

What is Statistics?

Why Study Statistics?

Uses of Statistics

Statistical Challenges

Writing and Presenting Reports

Critical Thinking

Statistics: An Evolving Field

Chapter1111

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What is Statistics?What is Statistics?

• StatisticsStatistics is the science of collecting, organizing, is the science of collecting, organizing, analyzing, interpreting, and presenting data.analyzing, interpreting, and presenting data.

• AA statisticstatistic is a single measure (number) used to is a single measure (number) used to summarize a sample data set. For example, the summarize a sample data set. For example, the average height of students in this class.average height of students in this class.

• AA statisticianstatistician is an expert with at least a master’s is an expert with at least a master’s degree in mathematics or statistics or a trained degree in mathematics or statistics or a trained professional in a related field.professional in a related field.

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Why Study Statistics?Why Study Statistics?

CommunicationCommunication

Computer SkillsComputer Skills

Understanding the language of statistics facilitates communication and improves problem solving.

The use of spreadsheets for data analysis and word processors or presentation software for reports improves upon your existing skills.

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Information ManagementInformation Management

Technical LiteracyTechnical Literacy

Statistics help summarize large amounts of data and reveal underlying relationships.

Career opportunities are in growth industries propelled by advanced technology. The use of statistical software increases your technical literacy.

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Career AdvancementCareer Advancement

Quality ImprovementQuality Improvement

Statistical literacy can enhance your career mobility.

Statistics helps firms oversee their suppliers, monitor their internal operations and identify problems.

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Uses of StatisticsUses of Statistics

Two primary kinds of statistics:Two primary kinds of statistics:

Descriptive statisticsDescriptive statistics – the collection, organization, presentation and summary of data.

Inferential statisticsInferential statistics – generalizing from a sample to a population, estimating unknown parameters, drawing conclusions, making decisions.

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Overview of Statistics Overview of Statistics (Figure 1.1)(Figure 1.1)

StatisticsStatistics

Collecting and Collecting and

Describing DataDescribing DataMaking InferencesMaking Inferences

from Samplesfrom Samples

Sampling

and SurveysVisual

DisplaysNumerical

Summaries

Probability

Models

Estimating

Parameters

Testing

HypothesesRegression

and Trends

Quality

Control

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AuditingAuditing

MarketingMarketing

Sample from over 12,000 invoices to estimate the proportion of incorrectly paid invoices.

Identify likely repeat customers for Amazon.com and suggests co-marketing opportunities based on a database of 5 million Internet purchases.

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Health CareHealth Care

Quality ControlQuality Control

Evaluate 100 incoming patients using a 42-item physical and mental assessment questionnaire.

Initiate a triple inspection program, setting penalties for workers who produce poor-quality output.

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PurchasingPurchasing

MedicineMedicine

Determine the defect rate of a shipment and whether that rate has changed significantly over time.

Determine whether a new drug is really better than the placebo or if the difference is due to chance.

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ForecastingForecasting

Product WarrantyProduct WarrantyDetermine the average dollar cost of engine

warranty claims on a new hybrid engine.

Manage inventory by forecasting consumer demand.

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Statistical ChallengesStatistical Challenges

• Is technically current (e.g., software-wise).Is technically current (e.g., software-wise).

• Communicates well.Communicates well.

• Is proactive.Is proactive.

• Has a broad outlook.Has a broad outlook.

• Is flexible.Is flexible.

• Focuses on the main problem.Focuses on the main problem.

The Ideal Data AnalystThe Ideal Data Analyst

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• Meets deadlines.Meets deadlines.

• Knows his/her limitations and is willing to Knows his/her limitations and is willing to ask for help.ask for help.

• Can deal with imperfect information.Can deal with imperfect information.

• Has professional integrity.Has professional integrity.

The Ideal Data AnalystThe Ideal Data Analyst

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Working with Imperfect DataWorking with Imperfect Data

Dealing with Practical ConstraintsDealing with Practical Constraints

State any assumptions and limitations and use generally accepted statistical tests to detect unusual data points or to deal with missing data.

You will face constraints on the type and quantity of data you can collect.

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Upholding Ethical StandardsUpholding Ethical Standards

Using ConsultantsUsing Consultants


Know and follow accepted procedures, maintain data integrity, carry out accurate calculations, report procedures, protect confidentiality, cite sources and financial support.

Hire consultants at the beginning of the project, when your team lacks certain skills or when an unbiased or informed view is needed.

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Skills Needed for Success in BusinessSkills Needed for Success in Business(Table 1.1)(Table 1.1)

For initial job success

For long-range job success

Common weaknesses

Report-writing Managerial accounting

Communication skills

Accounting principles

Managerial economics

Writing skills

Mathematics Managerial finance Immaturity

Statistics Oral communication

Unrealistic expectations

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Writing and Presenting ReportsWriting and Presenting Reports

Rules for Power WritingRules for Power Writing• Outline the report before you begin.

• Complete the report in sections.

• Ask trusted peers to review the report and make any necessary revisions.

• Be prepared to make multiple revisions.

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Writing StyleWriting Style• Answer research question succinctly.

• List most important results first.

• Include section headings and avoid lengthy paragraphs.

• Provide clear data sources.

• Use appendices for technical information.

• Be stylistically consistent.

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Avoid JargonAvoid Jargon

Make It AttractiveMake It Attractive

• Present technical concepts so that others Present technical concepts so that others can understand them.can understand them.

• Reports should have a title page, Reports should have a title page, descriptive title, date, and author names.descriptive title, date, and author names.

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Watch Your Spelling and GrammarWatch Your Spelling and Grammar

• Get someone you trust to red-pencil your Get someone you trust to red-pencil your work. Don’t rely on software to catch all work. Don’t rely on software to catch all spelling and grammar errors.spelling and grammar errors.

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Organizing a Technical ReportOrganizing a Technical ReportTypical business report style includes:

• Executive SummaryExecutive Summary (1 page maximum)- Briefly describe task and goals, data and data sources, methods that were used, main findings and any limitations.

• IntroductionIntroduction (1 to 3 paragraphs)- Statement of the problem- Data sources and definitions- Methods utilized

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Organizing a Technical ReportOrganizing a Technical ReportTypical business report style includes:

• Body of the ReportBody of the Report (as long as necessary)- Discussion, explanations, interpretations- Tables and graphs, as needed

• ConclusionsConclusions (1 to 3 paragraphs)- Statement of findings (in order of importance)- Limitations (if necessary)- Future research suggestions

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Organizing a Technical ReportOrganizing a Technical ReportTypical business report style includes:• Bibliography and SourcesBibliography and Sources

• AppendicesAppendices (if needed for lengthy or technical material)

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• Tables should be Tables should be embedded in the embedded in the narrative near the narrative near the paragraph in which paragraph in which they are interpreted.they are interpreted.

• Number and title Number and title each table above the each table above the table, each graph table, each graph below the graph.below the graph.

Tables and GraphsTables and Graphs

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Rules for Presenting Oral ReportsRules for Presenting Oral ReportsSelect a few key points to convey.

Use simple charts and diagrams.

Emphasize using color and fonts creatively.

Have backup slides or transparencies.

Rehearse timing.

Refer audience to written report for details.

Imagine yourself in the audience.

Avoid gratuitous jokes.

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The Three PsThe Three Ps• PacePace yourself when presenting. Take your

time, introduce yourself, your data and your project. Make the first minute count.

• PlanPlan what your are going to present. Organize your ideas with an outline. Keep it simple!

• PracticePractice before presenting to get the timing right. Consider videotaping yourself or practicing in front of peers.

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Pictures Help Make the PointPictures Help Make the Point

(Figure 1.3)

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Critical ThinkingCritical Thinking

• Statistics is an essential part of critical critical thinkingthinking because it allows us to test an idea against empirical evidence.

• Empirical DataEmpirical Data represent data collected through observation and experiments.

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Pitfall 1: Making Conclusions about a Pitfall 1: Making Conclusions about a Large Population from a Small SampleLarge Population from a Small Sample

Pitfall 2: Making Conclusions fromPitfall 2: Making Conclusions from Nonrandom Samples Nonrandom Samples

Be careful about making generalizations from small samples (e.g., a group of 10 patients).

Be careful about making generalizations from retrospective studies of special groups (e.g., heart attack patients).

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Pitfall 3: Conclusions From Rare EventsPitfall 3: Conclusions From Rare Events

Pitfall 4: Using Poor Survey MethodsPitfall 4: Using Poor Survey Methods

Be careful about drawing strong inferences from events that are not surprising when looking at the entire population (e.g., winning the lottery).

Be careful about using poor sampling methods or vaguely worded questions (e.g., anonymous survey or quiz).

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Pitfall 5: Assuming a Causal Link Based Pitfall 5: Assuming a Causal Link Based on Observationson Observations

Pitfall 6: Making Generalizations about Pitfall 6: Making Generalizations about Individuals from Observations about Individuals from Observations about GroupsGroups

Be careful about drawing conclusions when no cause-and-effect link exists (e.g., most shark attacks occur between 12p.m. and 2p.m.).

Avoid reading too much into statistical generalizations (e.g., men are taller than women).

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Pitfall 7: Unconscious BiasPitfall 7: Unconscious Bias

Pitfall 8: Significance versus Pitfall 8: Significance versus ImportanceImportance

Be careful about unconsciously or subtly allowing bias to color handling of data (e.g., heart disease in men vs. women).

Statistically significant effects may lack practical importance (e.g., Austrian military recruits born in the spring average 0.6 cm taller than those born in the fall).

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Statistics: An Evolving FieldStatistics: An Evolving Field

• Statistics is a relatively young field, having been Statistics is a relatively young field, having been developed mostly during the 20developed mostly during the 20thth century. century.

• Its mathematical frontiers continue to expand with Its mathematical frontiers continue to expand with the aid of computers.the aid of computers.

• Major recent developments includeMajor recent developments include- Exploratory data analysis (EDA)- Exploratory data analysis (EDA)- Computer-intensive statistics- Computer-intensive statistics- Design of experiments- Design of experiments- Robust product design- Robust product design- Advanced Bayesian methods- Advanced Bayesian methods- Graphical Methods…and more- Graphical Methods…and more

Applied Statistics in Applied Statistics in Business & EconomicsBusiness & Economics

End of Chapter 1End of Chapter 1

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a powerpoint presentation package to accompany applied statistics in business & economics 2 nd...

Documents

study statistics

applied statistics

descriptive statistics

language of statistics

inferential statistics

primary kinds of statistics

presenting data

data analysis