General Business 704 Data Analysis for Managers Introduction The Course, Data, and Excel.

General Business 704General Business 704Data Analysis for Data Analysis for

ManagersManagers

General Business 704General Business 704Data Analysis for Data Analysis for

ManagersManagers

IntroductionIntroduction

The Course, Data, and ExcelThe Course, Data, and Excel

Instructor/Class InfoInstructor/Class InfoInstructor/Class InfoInstructor/Class Info

Kholid eFendiKholid [email protected]@hotmail.com

Class:Class:http://ins2happy.awardspace.comhttp://ins2happy.awardspace.com

Kholid eFendiKholid [email protected]@hotmail.com

Class:Class:http://ins2happy.awardspace.comhttp://ins2happy.awardspace.com

Course ObjectivesCourse ObjectivesCourse ObjectivesCourse Objectives

Master key terminology for data analysisMaster key terminology for data analysis Understand key statistical conceptsUnderstand key statistical concepts Master the selection of appropriate Master the selection of appropriate

statistical toolsstatistical tools Master the use of Excel for the Master the use of Excel for the

calculation of statisticscalculation of statistics Master the ability to interpret and explain Master the ability to interpret and explain

the meaning of statistical findingsthe meaning of statistical findings Have funHave fun

Class MottoClass MottoClass MottoClass Motto

We will learn no statisticWe will learn no statistic

before its timebefore its time

Our focus is on making sense of managerial situations and questions

through the use of statistics

Our focus is on making sense of managerial situations and questions

through the use of statistics

Course TopicsCourse TopicsCourse TopicsCourse Topics DataData ExcelExcel Presenting & Describing DataPresenting & Describing Data Estimation: Confidence IntervalsEstimation: Confidence Intervals Hypothesis TestingHypothesis Testing Simple Regression & CorrelationSimple Regression & Correlation Multiple RegressionMultiple Regression Bonus Session: Time Series, Bonus Session: Time Series,

Forecasting, & SmoothingForecasting, & Smoothing

Readings & Class TimeReadings & Class TimeReadings & Class TimeReadings & Class Time Reading AssignmentsReading Assignments

Ch. 4 & 5 review on your ownCh. 4 & 5 review on your own Ch. 10 covered in OIM 768: Quality Mgmt Ch. 1, Ch. 10 covered in OIM 768: Quality Mgmt Ch. 1,

1S, 2, 3, 6, 7, 8, & 9 overview1S, 2, 3, 6, 7, 8, & 9 overview Ch. 11 & 12 covered in depthCh. 11 & 12 covered in depth Ch. 13 for reference purposesCh. 13 for reference purposes

Class TimeClass Time Lecture & DiscussionLecture & Discussion DemonstrationsDemonstrations Application PracticeApplication Practice

AssignmentsAssignmentsAssignmentsAssignments

HomeworkHomework Demonstrate ability to do requested tasksDemonstrate ability to do requested tasks

Individual & Team CasesIndividual & Team Cases Demonstrate ability to: identify & apply Demonstrate ability to: identify & apply

appropriate tools; & interpret/explain findingsappropriate tools; & interpret/explain findings

Team ProjectTeam Project Demonstrate ability to: develop good questions; Demonstrate ability to: develop good questions;

identify appropriate data; identify & apply identify appropriate data; identify & apply appropriate tools; & interpret/explain findingsappropriate tools; & interpret/explain findings

ExamsExamsExamsExams

Exam #1Exam #1 Wednesday 9/23Wednesday 9/23 Covers material through Chapter 9Covers material through Chapter 9

Final ExamFinal Exam Wednesday 10/21Wednesday 10/21 Covers all course materialCovers all course material

GradingGradingGradingGrading

ActivityActivity PointsPointsHomework #1Homework #1 50 50Homework #2Homework #2 50 50Homework #3Homework #3 50 50Individual Case #1Individual Case #1 100 100Individual Case #2Individual Case #2 100 100Team CaseTeam Case 100 100Team ProjectTeam Project 250 250Exam #1Exam #1 100 100Final ExamFinal Exam 200 200

TOTAL POINTSTOTAL POINTS 10001000

ActivityActivity PointsPointsHomework #1Homework #1 50 50Homework #2Homework #2 50 50Homework #3Homework #3 50 50Individual Case #1Individual Case #1 100 100Individual Case #2Individual Case #2 100 100Team CaseTeam Case 100 100Team ProjectTeam Project 250 250Exam #1Exam #1 100 100Final ExamFinal Exam 200 200

TOTAL POINTSTOTAL POINTS 10001000

Objectives:Objectives:Data & ExcelData & ExcelObjectives:Objectives:

Data & ExcelData & Excel

Define statisticsDefine statistics Distinguish descriptive & inferential Distinguish descriptive & inferential

statisticsstatistics Summarize the sources of dataSummarize the sources of data Describe the types of data & scalesDescribe the types of data & scales Explain the types of samplesExplain the types of samples Describe survey process & errorsDescribe survey process & errors Discuss the use of ExcelDiscuss the use of Excel

Some Important IssuesSome Important IssuesSome Important IssuesSome Important Issues

Collecting dataCollecting data e.g., Surveye.g., Survey

Presenting dataPresenting data e.g., Charts & e.g., Charts &

tablestables

Characterizing Characterizing datadata e.g., Averagee.g., Average

Data Data AnalysisAnalysis

Decision-Decision-MakingMaking

© 1984-1994 T/Maker Co.

© 1984-1994 T/Maker Co.

Why?Why?

Application AreasApplication AreasApplication AreasApplication Areas

AccountingAccounting AuditingAuditing CostingCosting

FinanceFinance Financial trendsFinancial trends ForecastingForecasting

ManagementManagement Describe employeesDescribe employees Quality improvementQuality improvement

MarketingMarketing Consumer preferencesConsumer preferences Marketing mix effectsMarketing mix effects

Statistical MethodsStatistical MethodsStatistical MethodsStatistical Methods

StatisticalMethods

DescriptiveStatistics

InferentialStatistics

StatisticalMethods

DescriptiveStatistics

InferentialStatistics

Descriptive StatisticsDescriptive StatisticsDescriptive StatisticsDescriptive Statistics

InvolvesInvolves Collecting dataCollecting data Presenting dataPresenting data Characterizing Characterizing

datadata

PurposePurpose Describe dataDescribe data

X = 30.5 SX = 30.5 S22 = 113 = 113

0

25

50

Q1 Q2 Q3 Q4

$

0

25

50

Q1 Q2 Q3 Q4

$

__

Inferential StatisticsInferential StatisticsInferential StatisticsInferential Statistics

InvolvesInvolves EstimationEstimation Hypothesis Hypothesis

testingtesting

PurposePurpose Make decisions Make decisions

about population about population characteristicscharacteristics

Population?Population?

Population (universe)Population (universe) All items of interestAll items of interest

SampleSample Portion of populationPortion of population

ParameterParameter Summary measure about populationSummary measure about population

StatisticStatistic Summary measure about sampleSummary measure about sample

Some Key TermsSome Key TermsSome Key TermsSome Key Terms

• PP in in PPopulation opulation & & PParameterarameter

• SS in in SSample ample & & SStatistictatistic

Why Collect Data?Why Collect Data?Why Collect Data?Why Collect Data?

Obtain input to a research studyObtain input to a research study Measure performanceMeasure performance Assist in formulating decision Assist in formulating decision

alternativesalternatives Satisfy curiositySatisfy curiosity

Knowledge for the sake of knowledgeKnowledge for the sake of knowledge

Data TypesData TypesData TypesData Types

Data

Numerical(Quantitative)

Categorical(Qualitative)

Discrete Continuous

Data

Numerical(Quantitative)

Categorical(Qualitative)

Discrete Continuous

Data Type ExamplesData Type ExamplesData Type ExamplesData Type Examples

NumericalNumerical DiscreteDiscrete

To how many magazines do you subscribe To how many magazines do you subscribe currently? ___ (Number)currently? ___ (Number)

Continuous Continuous How tall are you? ___ (Inches)How tall are you? ___ (Inches)

CategoricalCategorical Do you own savings bonds? __ Yes __ NoDo you own savings bonds? __ Yes __ No

Interval scaleInterval scale Equal intervalsEqual intervals No true 0No true 0 e.g., Degrees Celsiuse.g., Degrees Celsius MeasurementMeasurement

Ratio scaleRatio scale Equal intervalsEqual intervals True 0True 0 Meaningful ratiosMeaningful ratios e.g., Height in inchese.g., Height in inches

How Are Data How Are Data Measured?Measured?

How Are Data How Are Data Measured?Measured?

Nominal scaleNominal scale CategoriesCategories

e.g., Male-femalee.g., Male-female CountCount

Ordinal scaleOrdinal scale CategoriesCategories Ordering impliedOrdering implied

e.g., High-lowe.g., High-low CountCount

Data SourcesData SourcesData SourcesData Sources

DataSources

Primary Secondary

Experiment Published(& On-Line)

Survey Observation

DataSources

Primary Secondary

Experiment Published(& On-Line)

Survey Observation

Collect data Collect data (field work)(field work)

Prepare dataPrepare data EditEdit CodeCode

Analyze dataAnalyze data Interpret findingsInterpret findings Report resultsReport results

Define purposeDefine purpose Design Design

questionnairequestionnaire Select sample Select sample

designdesign Sample type Sample type Sample sizeSample size

Basic Survey StepsBasic Survey StepsBasic Survey StepsBasic Survey Steps

Questionnaire DesignQuestionnaire DesignQuestionnaire DesignQuestionnaire Design

Question contentQuestion content Mode of responseMode of response Question wordingQuestion wording Question sequenceQuestion sequence LayoutLayout Pilot testingPilot testing

© 1984-1994 T/Maker Co.

Why Sample?Why Sample?Why Sample?Why Sample?

Destruction of test Destruction of test unitsunits Quality controlQuality control

Accurate & Accurate & reliable resultsreliable results

Pragmatic reasonsPragmatic reasons TimeTime CostCost

Types of SamplesTypes of SamplesTypes of SamplesTypes of Samples

Type ofSample

ProbabilityNon

Probability

SimpleRandom

StratifiedSystematic Cluster

ChunkJudg-ment

Quota

Type ofSample

ProbabilityNon

Probability

SimpleRandom


ChunkJudg-ment

Quota

Simple Simple Random SampleRandom Sample

Simple Simple Random SampleRandom Sample

Each population element Each population element has an has an equal chanceequal chance of of being selectedbeing selected

Selecting 1 subject does Selecting 1 subject does not affect selecting not affect selecting othersothers

May use random number May use random number table, lottery, ‘fish bowl’table, lottery, ‘fish bowl’

© 1984-1994 T/Maker Co.

Random Number Random Number TableTable

Random Number Random Number TableTable

Column

00000 00001 11111 11111Row 12345 67890 12345 67890

01 49280 88924 35779 00283

02 61870 41657 07468 08612

03 43898 65923 25078 86129

Column

00000 00001 11111 11111Row 12345 67890 12345 67890

01 49280 88924 35779 00283

02 61870 41657 07468 08612

03 43898 65923 25078 86129

OR: Use Excel to generate random numbersOR: Use Excel to generate random numbers


Type ofSample

ProbabilityNon

Probability

SimpleRandom


ChunkJudg-ment

Quota

Type ofSample

ProbabilityNon

Probability

SimpleRandom


ChunkJudg-ment

Quota

Systematic SampleSystematic SampleSystematic SampleSystematic Sample

Every Every kkth element Is th element Is selected after a selected after a random start within random start within the first the first kk elements elements

Skip interval, Skip interval, kk, is, is Population sizePopulation size Sample size Sample size

Used in telephone Used in telephone surveyssurveys © 1984-1994 T/Maker Co.


Type ofSample

ProbabilityNon

Probability

SimpleRandom


ChunkJudg-ment

Quota

Type ofSample

ProbabilityNon

Probability

SimpleRandom


ChunkJudg-ment

Quota

Stratified SampleStratified SampleStratified SampleStratified Sample

Divide population into Divide population into subgroupssubgroups Mutually exclusiveMutually exclusive ExhaustiveExhaustive At least 1 common At least 1 common

characteristic of characteristic of interestinterest

Select simple random Select simple random samples from samples from subgroupssubgroups

All StudentsAll Students

CommuterCommuterss

ResidentsResidents

SampleSample


Type ofSample

ProbabilityNon

Probability

SimpleRandom


ChunkJudg-ment

Quota

Type ofSample

ProbabilityNon

Probability

SimpleRandom


ChunkJudg-ment

Quota

Cluster SampleCluster SampleCluster SampleCluster Sample

Divide population Divide population into clustersinto clusters If managers If managers

are elements then are elements then companies are clusterscompanies are clusters

Select clusters Select clusters randomlyrandomly

Survey all or a random Survey all or a random sample of elements in sample of elements in clustercluster

Companies (Clusters)Companies (Clusters)

SampleSample


Type ofSample

ProbabilityNon

Probability

SimpleRandom


ChunkJudg-ment

Quota

Type ofSample

ProbabilityNon

Probability

SimpleRandom


ChunkJudg-ment

Quota

Nonprobability Nonprobability SamplesSamples

Nonprobability Nonprobability SamplesSamples

JudgmentJudgment Use experience to select sampleUse experience to select sample Example: Test marketsExample: Test markets

QuotaQuota Similar to stratified sampling Similar to stratified sampling

except no random samplingexcept no random sampling

Chunk (convenience)Chunk (convenience) Use elements most availableUse elements most available

Errors Due to Errors Due to Sampling Sampling

Errors Due to Errors Due to Sampling Sampling

Total Population(Students)

Sample Frame(Students inPhone Book)

Planned Sample(Selected Students)

ActualSample

Coverage (Frame) Error

Sampling Error

Nonresponse &Measurement Error

Total Population(Students)

Sample Frame(Students inPhone Book)

Planned Sample(Selected Students)

ActualSample

Coverage (Frame) Error

Sampling Error

Nonresponse &Measurement Error

The Use of ExcelThe Use of ExcelThe Use of ExcelThe Use of Excel

Microsoft Excel 97 Windows/ 98 MacMicrosoft Excel 97 Windows/ 98 Mac Graduate Lab has Excel 97Graduate Lab has Excel 97 Our analyses done with Excel 97/98Our analyses done with Excel 97/98 Data disk with book for practiceData disk with book for practice Study Chapter 1SStudy Chapter 1S Review update to 1S for Excel 97Review update to 1S for Excel 97

Objectives:Objectives:Data & ExcelData & ExcelObjectives:Objectives:

Data & ExcelData & Excel Define statisticsDefine statistics Distinguish descriptive & inferential Distinguish descriptive & inferential

statisticsstatistics Summarize the sources of dataSummarize the sources of data Describe the types of data & scalesDescribe the types of data & scales Explain the types of samplesExplain the types of samples Describe survey process & errorsDescribe survey process & errors Discuss the use of ExcelDiscuss the use of Excel

Course ObjectivesCourse ObjectivesCourse ObjectivesCourse Objectives

Master key terminology for data analysisMaster key terminology for data analysis Understand key statistical conceptsUnderstand key statistical concepts Master the selection of appropriate Master the selection of appropriate

statistical toolsstatistical tools Master the use of Excel for the Master the use of Excel for the

calculation of statisticscalculation of statistics Master the ability to interpret and explain Master the ability to interpret and explain

the meaning of statistical findingsthe meaning of statistical findings Have funHave fun

General Business 704 Data Analysis for Managers Introduction The Course, Data, and Excel.

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