Statistics for Business and Economics (EMEA Version) 5th edition

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David Anderson, Dennis J. Sweeney, Thomas Williams, Jeffrey D. Camm, James J. Cochran, James Freeman, and Eddie Shoesmith
Publisher: Cengage Learning

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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: Exercises (12)
    • 1: Case Problems
    • 1: Extra Problems (17)

  • Chapter 2: Descriptive Statistics: Tabular and Graphical Presentations
    • 2.1: Summarizing Categorical Data (8)
    • 2.2: Summarizing Quantitative Data (11)
    • 2.3: Summarizing Relationships Between Two Categorical Variables (4)
    • 2.4: Summarizing Relationships Between Two Quantitative Variables (3)
    • 2: Case Problems (5)
    • 2: Extra Problems (54)
    • 2: Exploring Statistics Applet Exercises (2)

  • Chapter 3: Descriptive Statistics: Numerical Measures
    • 3.1: Measures of Location (9)
    • 3.2: Measures of Variability (5)
    • 3.3: Measures of Distributional Shape, Relative Location, and Detecting Outliers (7)
    • 3.4: Exploratory Data Analysis (7)
    • 3.5: Measures of Association Between Two Variables (5)
    • 3: Case Problems (4)
    • 3: Extra Problems (46)
    • 3: Exploring Statistics Applet Exercises (2)

  • Chapter 4: Introduction to Probability
    • 4.1: Experiments, Counting Rules, and Assigning Probabilities (8)
    • 4.2: Events and Their Probabilities (4)
    • 4.3: Some Basic Relationships of Probability
    • 4.4: Conditional Probability (4)
    • 4.5: Bayes' Theorem (4)
    • 4: Case Problems (3)
    • 4: Extra Problems (43)
    • 4: Exploring Statistics Applet Exercises (2)

  • Chapter 5: Discrete Probability Distributions
    • 5.1: Random Variables (6)
    • 5.2: Discrete Probability Distributions (4)
    • 5.3: Expected Value and Variance (5)
    • 5.4: Bivariate Distributions, Covariance, and Financial Portfolios (4)
    • 5.5: Binomial Probability Distribution (2)
    • 5.6: Poisson Probability Distribution (3)
    • 5.7: Hypergeometric Probability Distribution (3)
    • 5: Case Problems (3)
    • 5: Extra Problems (45)
    • 5: Exploring Statistics Applet Exercises (1)

  • Chapter 6: Continuous Probability Distributions
    • 6.1: Uniform Probability Distribution (5)
    • 6.2: Normal Probability Distribution (8)
    • 6.3: Normal Approximation of Binomial Probabilities (2)
    • 6.4: Exponential Probability Distribution (4)
    • 6: Case Problems (2)
    • 6: Extra Problems (32)
    • 6: Exploring Statistics Applet Exercises (3)

  • Chapter 7: Sampling and Sampling Distributions
    • 7.1: The EAI Sampling Problem
    • 7.2: Simple Random Sampling (6)
    • 7.3: Point Estimation (4)
    • 7.4: Introduction to Sampling Distributions
    • 7.5: Sampling Distribution of (8)
    • 7.6: Sampling Distribution of P (7)
    • 7: Case Problems (1)
    • 7: Extra Problems (26)

  • Chapter 8: Interval Estimation
    • 8.1: Population Mean: σ Known (7)
    • 8.2: Population Mean: σ Unknown (12)
    • 8.3: Determining the Sample Size (6)
    • 8.4: Population Proportion (7)
    • 8: Case Problems (3)
    • 8: Extra Problems (36)
    • 8: Exploring Statistics Applet Exercises (9)

  • 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 (6)
    • 9.3: Further Discussion of Hypothesis-Testing Fundamentals (4)
    • 9.4: Population Mean With σ Unknown (6)
    • 9.5: Population Proportion (8)
    • 9.6: Type II Errors and Power (7)
    • 9: Case Problems (4)
    • 9: Extra Problems (48)
    • 9: Exploring Statistics Applet Exercises (1)

  • 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 (7)
    • 10.2: Inferences About the Difference Between Two Population Means: σ1 and σ2 Unknown (7)
    • 10.3: Inferences About the Difference Between Two Population Means: Matched Samples (5)
    • 10.4: Inferences About the Difference Between Two Population Proportions (6)
    • 10: Case Problems (2)
    • 10: Extra Problems (33)
    • 10: Exploring Statistics Applet Exercises (2)

  • Chapter 11: Inferences About Population Variances
    • 11.1: Inferences About a Population Variance (8)
    • 11.2: Inferences Comparing Two Population Variances (10)
    • 11: Case Problems (4)
    • 11: Extra Problems (28)
    • 11: Exploring Statistics Applet Exercises (2)

  • Chapter 12: Tests of Goodness of Fit and Independence
    • 12.1: Goodness of Fit Test: A Multinomial Population (4)
    • 12.2: Goodness of Fit Test: Poisson and Normal Distributions (3)
    • 12.3: Test of Independence (5)
    • 12: Case Problems (5)
    • 12: Extra Problems (34)
    • 12: Exploring Statistics Applet Exercises (1)

  • 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 (10)
    • 13.3: Multiple Comparison Procedures (6)
    • 13.4: Randomized Block Design (4)
    • 13.5: Factorial Experiment (4)
    • 13: Case Problems (6)
    • 13: Extra Problems (45)
    • 13: Exploring Statistics Applet Exercises (2)

  • Chapter 14: Simple Linear Regression
    • 14.1: Simple Linear Regression Model
    • 14.2: Least Squares Method (5)
    • 14.3: Coefficient of Determination (3)
    • 14.4: Model Assumptions
    • 14.5: Testing for Significance (5)
    • 14.6: Using the Estimated Regression Equation for Estimation and Prediction (3)
    • 14.7: Computer Solution (4)
    • 14.8: Residual Analysis: Validating Model Assumptions
    • 14.9: Residual Analysis: Autocorrelation (2)
    • 14.10: Residual Analysis: Outliers and Influential Observations (2)
    • 14: Case Problems (5)
    • 14: Extra Problems (54)
    • 14: Exploring Statistics Applet Exercises (5)

  • Chapter 15: Multiple Regression
    • 15.1: Multiple Regression Model
    • 15.2: Least Squares Method (7)
    • 15.3: Multiple Coefficient of Determination (7)
    • 15.4: Model Assumptions
    • 15.5: Testing for Significance (6)
    • 15.6: Using the Estimated Regression Equation for Estimation and Prediction (3)
    • 15.7: Qualitative Independent Variables (8)
    • 15.8: Residual Analysis (2)
    • 15.9: Logistic Regression (5)
    • 15: Case Problems (3)
    • 15: Extra Problems (30)

  • Chapter 16: Regression Analysis: Model Building
    • 16.1: General Linear Model (7)
    • 16.2: Determining When to Add or Delete Variables (5)
    • 16.3: Analysis of a Larger Problem
    • 16.4: Variable Selection Procedures (1)
    • 16: Case Problems (2)
    • 16: Extra Problems (21)
    • 16: Exploring Statistics Applet Exercises (1)

  • Chapter 17: Time Series Analysis and Forecasting
    • 17.1: Time Series Patterns
    • 17.2: Forecast Accuracy (5)
    • 17.3: Moving Averages and Exponential Smoothing (12)
    • 17.4: Trend Projection (4)
    • 17.5: Seasonality and Trend (6)
    • 17.6: Time Series Decomposition (5)
    • 17: Case Problems (4)
    • 17: Extra Problems (47)
    • 17: Exploring Statistics Applet Exercises (3)

  • Chapter 18: Non-parametric Methods
    • 18.1: Sign Test (4)
    • 18.2: Wilcoxon Signed-Rank Test (3)
    • 18.3: Mann–Whitney–Wilcoxon Test (5)
    • 18.4: Kruskal–Wallis Test (4)
    • 18.5: Rank Correlation (4)
    • 18: Case Problems (2)
    • 18: Extra Problems (37)

  • Chapter 19: Index Numbers
    • 19.1: Price Relatives
    • 19.2: Aggregate Price Index Numbers (4)
    • 19.3: Computing an Aggregate Price Index from Price Relatives (4)
    • 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 (2)
    • 19: Case Problems
    • 19: Extra Problems (12)
    • 19: Exploring Statistics Applet Exercises

  • Chapter 20: Statistical Methods for Quality Control
    • 20.1: Philosophies and Frameworks
    • 20.2: Statistical Process Control (4)
    • 20.3: Acceptance Sampling (4)
    • 20: Case Problems
    • 20: Extra Problems (9)
    • 20: Exploring Statistics Applet Exercises (2)

  • Chapter 21: Decision Analysis
    • 21.1: Problem Formulation
    • 21.2: Decision-Making with Probabilities (2)
    • 21.3: Decision Analysis with Sample Information (3)
    • 21.4: Computing Branch Probabilities Using Bayes' Theorem (2)
    • 21: Case Problems (2)
    • 21: Extra Problems (18)

  • 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 (4)
    • 22.5: Stratified Random Sampling (6)
    • 22.6: Cluster Sampling (4)
    • 22.7: Systematic Sampling
    • 22: Case Problems (1)
    • 22: Extra Problems (13)

  • Chapter 13E: Additional Practice: 13th Edition
    • 13th Edition Chapter 1: Data and Statistics (9)
    • 13th Edition Chapter 2: Descriptive Statistics: Tabular and Graphical Displays (1)
    • 13th Edition Chapter 3: Descriptive Statistics: Numerical Measures (10)
    • 13th Edition Chapter 4: Introduction to Probability (8)
    • 13th Edition Chapter 5: Discrete Probability Distributions (8)
    • 13th Edition Chapter 6: Continuous Probability Distributions (9)
    • 13th Edition Chapter 7: Sampling and Sampling Distributions (1)
    • 13th Edition Chapter 8: Interval Estimation
    • 13th Edition Chapter 9: Hypothesis Tests (8)
    • 13th Edition Chapter 10: Inference About Means and Proportions with Two Populations (9)
    • 13th Edition Chapter 11: Inferences About Population Variances (7)
    • 13th Edition Chapter 12: Comparing Multiple Proportions, Test of Independence and Goodness of Fit (5)
    • 13th Edition Chapter 13: Experimental Design and Analysis of Variance (9)
    • 13th Edition Chapter 14: Simple Linear Regression (9)
    • 13th Edition Chapter 15: Multiple Regression (8)
    • 13th Edition Chapter 16: Regression Analysis: Model Building (5)
    • 13th Edition Chapter 17: Time Series Analysis and Forecasting (9)
    • 13th Edition Chapter 18: Nonparametric Methods (3)
    • 13th Edition Chapter 19: Statistical Methods for Quality Control
    • 13th Edition Chapter 20: Index Numbers (7)


Drawing from the authors' unmatched experience as professors and consultants, Anderson/Sweeney/Williams/Camm/Cochran/Freeman/Shoesmith's Statistics for Business and Economics, 5th edition, delivers sound statistical methodology, a proven problem-scenario approach, and meaningful applications that clearly demonstrate how statistical information impacts decisions in actual business practice. More than 350 real business examples, relevant cases, and hands-on exercises present the latest statistical data and business information with unwavering accuracy.

An all new WebAssign online course management system is available with this powerful business statistics solution. WebAssign offers extensive content and interactive learning activities that will help your students master their subject. Its engaging practice problems and other learning tools, including labs, simulations and videos, bring the subjects to life and provide students with a full understanding of concepts.

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13E - Previous Edition Exercise
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CP - Case Problem


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Group Quantity Questions
Chapter 1: Data and Statistics
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Chapter 2: Descriptive Statistics: Tabular and Graphical Presentations
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Chapter 3: Descriptive Statistics: Numerical Measures
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Chapter 4: Introduction to Probability
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Chapter 5: Discrete Probability Distributions
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Chapter 6: Continuous Probability Distributions
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Chapter 7: Sampling and Sampling Distributions
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Chapter 8: Interval Estimation
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Chapter 9: Hypothesis Tests
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Chapter 10: Statistical Inference About Means and Proportions with Two Populations
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Chapter 11: Inferences About Population Variances
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Chapter 12: Tests of Goodness of Fit and Independence
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Chapter 13: Experimental Design and Analysis of Variance
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Chapter 13E: Additional Practice: 13th Edition
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Chapter 14: Simple Linear Regression
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14.CP 5 002 501.XP 501.XP.alt 502.XP 503.XP
14.E 24 001 002 003 004 005 007 008 009 013 014 015.MI 015.MI.SA 017 018 019 020 022 023 024.MI 024.MI.SA 025 026 029 030
14.XP 54 001 002 003 004 005 005.alt 006.MI 006.MI.SA 006.alt 007 008 008.alt 009.MI 009.MI.SA 010 011.MI 011.MI.SA 011.alt 012 013 014 015 015.alt 016 016.alt 017.MI 017.MI.SA 018 018.alt 019 019.alt 020 021 022 023 024 024.alt 025 025.alt 026 027.MI 027.MI.SA 028 028.alt 029 029.alt 030 030.alt 031 032 033 034 035 036
Chapter 15: Multiple Regression
15.CP 3 501.XP 501.XP.alt 502.XP
15.E 38 001 002 003 004.MI 004.MI.SA 005 006 007 008 009.MI 009.MI.SA 010 011 011.alt 012.MI 012.MI.SA 013 014 015 016 017 018 019 020 021 022.MI 022.MI.SA 023 023.alt 025.MI 025.MI.SA 026 027 030 031.MI 031.MI.SA 032 034
15.XP 30 001 002 003 003.alt 004 005 006 006.alt 007 008 009 009.alt 010 011 011.alt 012 013 013.alt 014 015 015.alt 016 017 018 019.MI 019.MI.SA 020 021 022 023
Chapter 16: Regression Analysis: Model Building
16.AQ 1 501
16.CP 2 003 501.XP
16.E 13 001 002 003 005 006 008 008.alt 009.MI 009.MI.SA 010.MI 010.MI.SA 011 015
16.XP 21 001 002.MI 002.MI.SA 002.alt 003 004 005 006 006.alt 007 008 009 010 011 012 013 013.alt 014 015 016 017
Chapter 17: Time Series Analysis and Forecasting
17.AQ 3 501 502 503
17.CP 4 001 001.alt 003 003.alt
17.E 32 001 002 003 004.MI 004.MI.SA 005 006 007 007.alt 008 008.alt 009 009.alt 010 011.MI 011.MI.SA 012 014 016 017 018 022 023 024 024.alt 025 025.alt 026.MI 026.MI.SA 027 028 028.alt
17.XP 47 001 002 003 004 005 005.alt 006.MI 006.MI.SA 007 007.alt 008.MI 008.MI.SA 008.alt 009 009.alt 010 010.alt 011 011.alt 012 012.alt 013 013.alt 014 014.alt 015 015.alt 016 016.alt 017 018 019 020 020.alt 021 022 022.alt 023 024 024.alt 025 026 027 028 028.alt 029 030
Chapter 18: Non-parametric Methods
18.CP 2 501.XP 501.XP.alt
18.E 20 002 004 006 007 009 010 011 013 013.alt 014 015 017 018 019 021 021.alt 022 023 024 026
18.XP 37 001 002 003 004 005.MI 005.MI.SA 006 007.MI 007.MI.SA 007.alt 008 008.alt 009 009.alt 010 011 011.alt 012.MI 012.MI.SA 013 014 014.alt 015 015.alt 016 016.alt 017 017.alt 018 019 020 020.alt 021 021.alt 022 022.alt 023
Chapter 19: Index Numbers
19.E 10 001 004.MI 004.MI.SA 006 009 010 011 012 018 019
19.XP 12 001 002.MI 002.MI.SA 003 004.MI 004.MI.SA 005 006 007.MI 007.MI.SA 008 008.alt
Chapter 20: Statistical Methods for Quality Control
20.AQ 2 501 502
20.E 8 001 003 004 007 010 011 013 014
20.XP 9 001 002.MI 002.MI.SA 003 004 005 006 007.MI 007.MI.SA
Chapter 21: Decision Analysis
21.CP 2 501.XP 502.XP
21.E 7 001 005 010 012 013 015 017
21.XP 18 001 002 003.MI 003.MI.SA 004.MI 004.MI.SA 005 006 007.MI 007.MI.SA 008 009.MI 009.MI.SA 010 011 012 013 014
Chapter 22: Sample Surveys
22.CP 1 501.XP
22.E 14 001 002 003 004 008 009.MI 009.MI.SA 010 011 012 014 015 016.MI 016.MI.SA
22.XP 13 001 002.MI 002.MI.SA 003 004 005 006 007 008 009 010 011 012
Total 1425 (1)