Getting, Describing, and Summarizing Data
Introduction to Data Analysis and Decision Making
Introduction
An Overview of the Book
The Methods
The Software
A Sampling of Examples
Modeling and Models
Conclusion
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
Describing Data: Summary Measures
Introduction
Measures of Central Location
Quartiles and Percentiles
Minimum, Maximum, and Range
Measures of Variability: Variance and Standard Deviation
Obtaining Summary Measures with StatTools
Measures of Association: Covariance and Correlation
Describing Data Sets with Boxplots
Applying the Tools
Conclusion
Getting the Right Data
Introduction
Sources of Data
Excel Tables for Filtering, Sorting, and Summarizing
Complex Queries with the Advanced Filter
Importing External Data from Access
Creating Pivot Tables from External Data
Web Queries
Other Data Sources on the Web
Cleansing the Data
Conclusion
Probability, Uncertainty, and Decision Making
Probability and Probability Distributions
Introduction
Probability Essentials
Distribution of a Single Random Variable
An Introduction to Simulation
Distribution of Two Random Variables: Scenario Approach
Distribution of Two Random Variables: Joint Probability Approach
Independent Random Variables
Weighted Sums of Random Variables
Conclusion
Normal, Binomial, Poisson, and Exponential Distributions
Introduction
The Normal Distribution
Applications of the Normal Distribution
The Binomial Distribution
Applications of the Binomial Distribution
The Poisson and Exponential Distributions
Fitting a Probability Distribution to Data: BestFit
Conclusion
Decision Making Under Uncertainty
Introduction
Elements of a Decision Analysis
The PrecisionTree Add-In
Bayes' Rule
Multistage Decision Problems
Incorporating Attitudes Toward Risk
Conclusion
Statistical Inference
Sampling and Sampling Distributions
Introduction
Sampling Terminology
Methods for Selecting Random Samples
An Introduction to Estimation
Conclusion
Confidence Interval Estimation
Introduction
Sampling Distributions
Confidence Interval for a Mean
Confidence Interval for a Total
Confidence Interval for a Proportion
Confidence Interval for a Standard Deviation
Confidence Interval for the Difference Between Means
Confidence Interval for the Difference Between Proportions Controlling Confidence Interval Length
Conclusion
Hypothesis Testing
Introduction
Concepts in Hypothesis Testing
Hypothesis Tests for a Population Mean
Hypothesis Tests for Other Parameters
Tests for Normality
Chi-Square Test for Independence
One-Way ANOVA
Conclusion
Regression, Forecasting, and Time Series
Regression Analysis: Estimating Relationships
Introduction
Scatterplots: Graphing Relationships
Correlations: Indicators of Linear Relationships Simple Linear Regression
Multiple Regression
Modeling Possibilities
Validation of the Fit
Conclusion
Regression Analysis: Statistical Inference Introduction
The Statistical Model
Inferences About the Regression Coefficients
Multicollinearity
Include/Exclude Decisions
Stepwise Regression.The Partial F Test
Outliers
Violations of Regression Assumptions
Prediction
Conclusion
Time Series Analysis and Forecasting
Introduction
Forecasting Methods: An Overview
Testing for Randomness
Regression-Based Trend Models
The Random Walk Model
Autoregression Models
Moving Averages
Exponential Smoothing
Seasonal Models
Winters' Exponential Smoothing Model
Conclusion
Decision Modeling
Introduction to Optimization Modeling
Introduction
Introduction to Optimization
A Two-Variable Model
Sensitivity Analysis Properties of Linear Models
Infeasibility and Unboundedness
A Product Mix Model
A Multiperio