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Data Analysis & Decision Making with Excel + The DecisionTools & StatTools Suite
The emphasis of the text is on data analysis, modeling, and spreadsheet use in statistics and management science. This text contains professional Excel software add-ins. The authors maintain the elements that have made this text a market leader in its first edition: clarity of writing, a teach-by-example approach, and complete Excel integration.
Contents:
Part
I: GETTING, DESCRIBING, AND SUMMARIZING DATA
Introduction to Data Analysis and Decision Making
1
Introduction
An Overview of the Book
The Methods
TheSoftware
A Sampling of Examples
Modeling and Models.Conclusion
2
Describing Data: Graphs and Tables
Introduction
Basic Concepts
Frequency Tables and Histograms.Analyzing Relationships with Scatterplots
Time Series Graphs.Exploring Data with Pivot Tables
Conclusion
3
Describing Data: Summary Measures
Introduction
Measures of Central Location
Quartiles andPercentiles
Minimum, Maximum, and Range
Measures of Variability:Variance and Standard Deviation
Obtaining Summary Measures withStatTools
Measures of Association: Covariance and Correlation.Describing Data Sets with Boxplots
Applying the Tools
Conclusion
4
Getting the Right Data
Introduction
Sources ofData
Using Excel'sAutoFilter
Complex Querieswith the Advanced Filter.Importing External Datafrom Access
CreatingPivot Tables fromExternal Data
WebQueries
Other DataSources on the Web.Cleansing the Data
Conclusion
Part II: Probability, Uncertainty, and Decision Making
5
Probability and Probability Distributions
Introduction
Probability Essentials.Distribution of a Single RandomVariable
An Introduction toSimulation
Distribution of TwoRandom Variables: ScenarioApproach
Distribution ofTwo Random Variables:Joint ProbabilityApproach
IndependentRandom Variables.Weighted Sums ofRandom Variables
Conclusion
6
Normal, Binomial, Poisson, and Exponential Distributions
Introduction
The Normal Distribution
Applications of the NormalDistribution
The Binomial Distribution
Applications of the BinomialDistribution
The Poisson and Exponential Distributions
Fitting aProbability Distribution to Data: BestFit
Conclusion
7
Decision Making Under Uncertainty
Introduction
Elements of aDecision Analysis
ThePrecisionTree Add-In.Bayes' Rule
MultistageDecision Problems
Incorporating Attitudes Toward Risk
Conclusion
Part III: Statistical Inference
8
Sampling and Sampling Distributions
Introduction
Sampling Terminology
Methods for Selecting RandomSamples
An Introduction to Estimation
Conclusion
9
Confidence Interval Estimation
Introduction
Sampling Distributions
Confidence Interval for a Mean.Confidence Interval for a Total
Confidence Interval for aProportion
Confidence Interval for a Standard Deviation
ConfidenceInterval for the Difference Between Means
Confidence Interval forthe Difference Between Proportions Controlling Confidence IntervalLength
Conclusion
10
Hypothesis Testing
Introduction
Conceptsin Hypothesis Testing.Hypothesis Tests fora Population Mean.Hypothesis Testsfor OtherParameters.Tests forNormality.Chi-SquareTest forIndependence.One-WayANOVA
Conclusion
Part IV: Regression, Forecasting, and Time Series
11
Regression Analysis: Estimating Relationships
Introduction
Scatterplots: Graphing Relationships
Correlations:Indicators of Linear Relationships Simple Linear Regression
MultipleRegression
Modeling Possibilities
Validation of the Fit
Conclusion
12
Regression Analysis: Statistical Inference Introduction
TheStatistical Model
Inferences About the Regression Coefficients.Multicollinearity
Include/Exclude Decisions
Stepwise Regression.ThePartial F Test
Outliers
Violations of Regression Assumptions.Prediction
Conclusion
13
Time Series Analysis and Forecasting
Introduction.Forecasting Methods:An Overview
Testingfor Randomness.Regression-BasedTrend Models
TheRandom Walk Model.Autoregression Models.Moving Averages.ExponentialSmoothing.SeasonalModels.Winters'Exponential Smoothing Model
Conclusion
Part V: Decision Modeling
14
Introduction to Optimization Modeling
Introduction
Introduction to Optimization
ATwo-Variable Model
Sensitivity AnalysisProperties of Linear Models
Infeasibility and Unboundedness
AProduct Mix Model
A Multiperiod Production Model
A Comparisonof Algebraic and Spreadsheet Models
A Decision Support System.Conclusion
15
Optimization Modeling: Applications
Introduction
Workforce SchedulingModels
Blending Models
Logistics Models
Aggregate PlanningModels
Financial Models
Integer Programming Models
NonlinearModels
Conclusion
16.Introduction to Simulation Modeling
Introduction
Real Applicationsof Simulation
ProbabilityDistributions for InputVariables
Simulationwith Built-In ExcelTools
Introduction to@RISK
The Effects ofInput Distributions on Results
Conclusion
17.Simulation Models
Introduction
Operations Models
Financial Models
MarketingModels
Simulating Games of Chance
Conclusion.
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