Statistics for Business and Economics (EMEA Version) 6th edition

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• Chapter 1: Data and Statistics
  • 1.1: Applications in Business and Economics
  • 1.2: Data
  • 1.3: Data Sources
  • 1.4: Descriptive Statistics
  • 1.5: Statistical Inference
  • 1.6: Analytics
  • 1.7: Big Data and Data Mining
  • 1.8: Computers and Statistical Analysis
  • 1.9: Ethical Guidelines for Statistical Practice
  • 1: Exercises
  • 1: Case Problems
  • 1: Extra Problems
  
  
• Chapter 2: Descriptive Statistics: Tabular and Graphical Presentations
  • 2.1: Summarizing Categorical Data
  • 2.2: Summarizing Quantitative Data
  • 2.3: Summarizing Relationships Between Two Categorical Variables
  • 2.4: Summarizing Relationships Between Two Quantitative Variables
  • 2.5: Data Visualization: Best Practices in Creating Effective Graphical Displays
  • 2: Case Problems
  • 2: Extra Problems
  • 2: Exploring Statistics Applet Exercises
  
  
• Chapter 3: Descriptive Statistics: Numerical Measures
  • 3.1: Measures of Location
  • 3.2: Measures of Variability
  • 3.3: Measures of Distributional Shape, Relative Location, and Detecting Outliers
  • 3.4: Exploratory Data Analysis
  • 3.5: Measures of Association Between Two Variables
  • 3.6: Data Dashboards: Adding Numerical Measures To Improve Effectiveness
  • 3: Case Problems
  • 3: Extra Problems
  • 3: Exploring Statistics Applet Exercises
  
  
• Chapter 4: Introduction to Probability
  • 4.1: Experiments, Counting Rules and Assigning Probabilities
  • 4.2: Events and Their Probabilities
  • 4.3: Some Basic Relationships of Probability
  • 4.4: Conditional Probability
  • 4.5: Bayes' Theorem
  • 4: Case Problems
  • 4: Extra Problems
  • 4: Exploring Statistics Applet Exercises
  
  
• Chapter 5: Discrete Probability Distributions
  • 5.1: Random Variables
  • 5.2: Discrete Probability Distributions
  • 5.3: Expected Value and Variance
  • 5.4: Bivariate Distributions, Covariance and Financial Portfolios
  • 5.5: Binomial Probability Distribution
  • 5.6: Poisson Probability Distribution
  • 5.7: Hypergeometric Probability Distribution
  • 5: Case Problems
  • 5: Extra Problems
  • 5: Exploring Statistics Applet Exercises
  
  
• Chapter 6: Continuous Probability Distributions
  • 6.1: Uniform Probability Distribution
  • 6.2: Normal Probability Distribution
  • 6.3: Normal Approximation of Binomial Probabilities
  • 6.4: Exponential Probability Distribution
  • 6: Case Problems
  • 6: Extra Problems
  • 6: Exploring Statistics Applet Exercises
  
  
• Chapter 7: Sampling and Sampling Distributions
  • 7.1: The EAI Sampling Problem
  • 7.2: Simple Random Sampling
  • 7.3: Point Estimation
  • 7.4: Introduction to Sampling Distributions
  • 7.5: Sampling Distribution of X̄
  • 7.6: Sampling Distribution of P
  • 7.7: Big Data and Standard Errors of Sampling Distributions
  • 7: Case Problems
  • 7: Extra Problems
  
  
• Chapter 8: Interval Estimation
  • 8.1: Population Mean: σ Known
  • 8.2: Population Mean: σ Unknown
  • 8.3: Determining the Sample Size
  • 8.4: Population Proportion
  • 8.5: Big Data and Confidence Intervals
  • 8: Case Problems
  • 8: Extra Problems
  • 8: Exploring Statistics Applet Exercises
  
  
• Chapter 9: Hypothesis Tests
  • 9.1: Testing a Population Mean with σ Known: One-Tailed Test
  • 9.2: Testing a Population Mean with σ Known: Two-Tailed Test
  • 9.3: Further Discussion of Hypothesis-Testing Fundamentals
  • 9.4: Population Mean With σ Unknown
  • 9.5: Population Proportion
  • 9.6: Type II Errors and Power
  • 9.7: Big Data and Hypothesis Testing
  • 9: Case Problems
  • 9: Extra Problems
  • 9: Exploring Statistics Applet Exercises
  
  
• Chapter 10: Statistical Inference About Means and Proportions with Two Populations
  • 10.1: Inferences About the Difference Between Two Population Means: σ₁ and σ₂ Known
  • 10.2: Inferences About the Difference Between Two Population Means: σ₁ and σ₂ Unknown
  • 10.3: Inferences About the Difference Between Two Population Means: Matched Samples
  • 10.4: Inferences About the Difference Between Two Population Proportions
  • 10: Case Problems
  • 10: Extra Problems
  • 10: Exploring Statistics Applet Exercises
  
  
• Chapter 11: Inferences About Population Variances
  • 11.1: Inferences About a Population Variance
  • 11.2: Inferences Comparing Two Population Variances
  • 11: Case Problems
  • 11: Extra Problems
  • 11: Exploring Statistics Applet Exercises
  
  
• Chapter 12: Tests of Goodness of Fit and Independence
  • 12.1: Goodness of Fit Test: A Multinomial Population
  • 12.2: Goodness of Fit Test: Poisson and Normal Distributions
  • 12.3: Test of Independence
  • 12: Case Problems
  • 12: Extra Problems
  • 12: Exploring Statistics Applet Exercises
  
  
• Chapter 13: Experimental Design and Analysis of Variance
  • 13.1: An Introduction to Experimental Design and Analysis of Variance
  • 13.2: Analysis of Variance and the Completely Randomized Design
  • 13.3: Multiple Comparison Procedures
  • 13.4: Randomized Block Design
  • 13.5: Factorial Experiment
  • 13: Case Problems
  • 13: Extra Problems
  • 13: Exploring Statistics Applet Exercises
  
  
• Chapter 14: Simple Linear Regression
  • 14.1: Simple Linear Regression Model
  • 14.2: Least Squares Method
  • 14.3: Coefficient of Determination
  • 14.4: Model Assumptions
  • 14.5: Testing for Significance
  • 14.6: Using the Estimated Regression Equation for Estimation and Prediction
  • 14.7: Computer Solution
  • 14.8: Residual Analysis: Validating Model Assumptions
  • 14.9: Residual Analysis: Autocorrelation
  • 14.10: Residual Analysis: Outliers and Influential Observations
  • 14.11: Practical Advice: Big Data and Hypothesis Testing in Simple Linear Regression
  • 14: Case Problems
  • 14: Extra Problems
  • 14: Exploring Statistics Applet Exercises
  
  
• Chapter 15: Multiple Regression
  • 15.1: Multiple Regression Model
  • 15.2: Least Squares Method
  • 15.3: Multiple Coefficient of Determination
  • 15.4: Model Assumptions
  • 15.5: Testing for Significance
  • 15.6: Using the Estimated Regression Equation for Estimation and Prediction
  • 15.7: Categorical Independent Variables
  • 15.8: Residual Analysis
  • 15.9: Logistic Regression
  • 15.10: Practical Advice: Big Data and Hypothesis Testing in Multiple Regression
  • 15: Case Problems
  • 15: Extra Problems
  
  
• Chapter 16: Regression Analysis: Model Building
  • 16.1: General Linear Model
  • 16.2: Determining When to Add or Delete Variables
  • 16.3: Analysis of a Larger Problem
  • 16: Case Problems
  • 16: Extra Problems
  • 16: Exploring Statistics Applet Exercises
  
  
• Chapter 17: Time Series Analysis and Forecasting
  • 17.1: Time Series Patterns
  • 17.2: Forecast Accuracy
  • 17.3: Moving Averages and Exponential Smoothing
  • 17.4: Trend Projection
  • 17.5: Seasonality and Trend
  • 17.6: Time Series Decomposition
  • 17: Case Problems
  • 17: Extra Problems
  • 17: Exploring Statistics Applet Exercises
  
  
• Chapter 18: Non-Parametric Methods
  • 18.1: Sign Test
  • 18.2: Wilcoxon Signed-Rank Test
  • 18.3: Mann–Whitney–Wilcoxon Test
  • 18.4: Kruskal–Wallis Test
  • 18.5: Rank Correlation
  • 18: Case Problems
  • 18: Extra Problems
  
  
• Chapter 19: Index Numbers
  • 19.1: Price Relatives
  • 19.2: Aggregate Price Index Numbers
  • 19.3: Computing an Aggregate Price Index from Price Relatives
  • 19.4: Some Important Price Index Numbers
  • 19.5: Deflating a Series Using a Price Index Number
  • 19.6: Price Index Numbers: Other Considerations
  • 19.7: Quantity Index Numbers
  • 19: Case Problems
  • 19: Extra Problems
  
  
• Chapter 20: Statistical Methods for Quality Control
  • 20.1: Philosophies and Frameworks
  • 20.2: Statistical Process Control
  • 20.3: Acceptance Sampling
  • 20: Case Problems
  • 20: Extra Problems
  • 20: Exploring Statistics Applet Exercises
  
  
• Chapter 21: Decision Analysis
  • 21.1: Problem Formulation
  • 21.2: Decision-Making with Probabilities
  • 21.3: Decision Analysis with Sample Information
  • 21.4: Computing Branch Probabilities Using Bayes' Theorem
  • 21: Case Problems
  • 21: Extra Problems
  
  
• Chapter 22: Sample Surveys
  • 22.1: Terminology Used in Sample Surveys
  • 22.2: Types of Surveys and Sampling Methods
  • 22.3: Survey Errors
  • 22.4: Simple Random Sampling
  • 22.5: Stratified Random Sampling
  • 22.6: Cluster Sampling
  • 22.7: Systematic Sampling
  • 22: Case Problems
  • 22: Extra Problems
  
  
• Chapter 13E: Additional Practice: 13th Edition
  • 13th Edition Chapter 1: Data and Statistics
  • 13th Edition Chapter 2: Descriptive Statistics: Tabular and Graphical Displays
  • 13th Edition Chapter 3: Descriptive Statistics: Numerical Measures
  • 13th Edition Chapter 4: Introduction to Probability
  • 13th Edition Chapter 5: Discrete Probability Distributions
  • 13th Edition Chapter 6: Continuous Probability Distributions
  • 13th Edition Chapter 7: Sampling and Sampling Distributions
  • 13th Edition Chapter 8: Interval Estimation
  • 13th Edition Chapter 9: Hypothesis Tests
  • 13th Edition Chapter 10: Inference About Means and Proportions with Two Populations
  • 13th Edition Chapter 11: Inferences About Population Variances
  • 13th Edition Chapter 12: Comparing Multiple Proportions, Test of Independence and Goodness of Fit
  • 13th Edition Chapter 13: Experimental Design and Analysis of Variance
  • 13th Edition Chapter 14: Simple Linear Regression
  • 13th Edition Chapter 15: Multiple Regression
  • 13th Edition Chapter 16: Regression Analysis: Model Building
  • 13th Edition Chapter 17: Time Series Analysis and Forecasting
  • 13th Edition Chapter 18: Nonparametric Methods
  • 13th Edition Chapter 19: Statistical Methods for Quality Control
  • 13th Edition Chapter 20: Index Numbers