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Statistics for Business and Economics, CourseSmart eTextbook, 12th Edition

By James T. McClave, P. George Benson, Terry Sincich

Published by Pearson

Published Date: Apr 23, 2013

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For a one- or two-semester course in business statistics.


Statistics for Business and Economics, Twelfth Edition, meets today's business students with a balance of clarity and rigor, and applications incorporated from a diverse range of industries. This classic text covers a wide variety of data collection and analysis techniques with these goals in mind: developing statistical thinking, learning to assess the credibility and value of inferences made from data, and making informed business decisions.


The Twelfth Edition has been updated with real, current data in many of the exercises, examples, and applications. Exercises draw on actual business situations and recent economic events so that students can test their knowledge throughout the course. Statistics in Action case studies open each chapter with a recent, controversial, or high-profile business issue, motivating students to critically evaluate the findings and think through the statistical issues involved. A continued emphasis on ethics highlights the importance of ethical behavior in collecting, interpreting, and reporting on data.


Table of Contents

1. Statistics, Data, and Statistical Thinking

1.1 The Science of Statistics

1.2 Types of Statistical Applications in Business

1.3 Fundamental Elements of Statistics

1.4 Processes (Optional)

1.5 Types of Data

1.6 Collecting Data: Sampling and Related Issues

1.7 Critical Thinking with Statistics

            Statistics in Action: A 20/20 View of Surveys: Fact or Fiction?

            Activity 1.1: Keep the Change: Collecting Data

            Activity 2.2: Identifying Misleading Statistics

            Using Technology: Accessing and Listing Data; Random Sampling


2. Methods for Describing Sets of Data

2.1 Describing Qualitative Data

2.2 Graphical Methods for Describing Quantitative Data

2.3 Numerical Measures of Central Tendency

2.4 Numerical Measures of Variability

2.5 Using the Mean and Standard Deviation to Describe Data

2.6 Numerical Measures of Relative Standing

2.7 Methods for Detecting Outliers: Box Plots and z-Scores

2.8 Graphing Bivariate Relationships (Optional)

2.9 The Time Series Plot (Optional)

2.10 Distorting the Truth with Descriptive Techniques

            Statistics in Action: Can Money Buy Love?

            Activity 2.1: Real Estate Sales

            Activity 2.2: Keep the Change: Measures of Central Tendency and Variability

            Using Technology: Describing Data

            Making Business Decisions: The Kentucky Milk CasePart 1 (Covers Chapters 1 and 2)


3. Probability

3.1 Events, Sample Spaces, and Probability

3.2 Unions and Intersections

3.3 Complementary Events

3.4 The Additive Rule and Mutually Exclusive Events

3.5 Conditional Probability

3.6 The Multiplicative Rule and Independent Events

3.7 Bayes’s Rule

            Statistics in Action: Lotto Buster!

            Activity 3.1: Exit Polls: Conditional Probability

            Activity 3.2: Keep the Change: Independent Events

            Using Technology: Combinations and Permutations


4. Random Variables and Probability Distributions

4.1 Two Types of Random Variables

PART I: Discrete Random Variables

4.2 Probability Distributions for Discrete Random Variables

4.3 The Binomial Distribution

4.4 Other Discrete Distributions: Poisson and Hypergeometric

PART II: Continuous Random Variables

4.5 Probability Distributions for Continuous Random Variables

4.6 The Normal Distribution

4.7 Descriptive Methods for Assessing Normality

4.8 Other Continuous Distributions: Uniform and Exponential

            Statistics in Action: Probability in a Reverse Cocaine Sting: Was Cocaine Really Sold?

            Activity 4.1: Warehouse Club Memberships: Exploring a Binomial Random Variable

            Activity 4.2: Identifying the Type of Probability Distribution

            Using Technology: Discrete Probabilities, Continuous Probabilities, and Normal Probability Plots


5. Sampling Distributions

5.1 The Concept of a Sampling Distribution

5.2 Properties of Sampling Distributions: Unbiasedness and Minimum Variance

5.3 The Sampling Distribution of the Sample Mean and the Central Limit Theorem

5.4 The Sampling Distribution of the Sample Proportion

            Statistics in Action: The Insomnia Pill: Is It Effective?

            Activity 5.1: Simulating a Sampling DistributionCell Phone Usage

            Using Technology: Simulating a Sampling Distribution

            Making Business Decisions: The Furniture Fire Case (Covers Chapters 3–5)


6. Inferences Based on a Single Sample: Estimation with Confidence Intervals

6.1 Identifying and Estimating the Target Parameter

6.2 Confidence Interval for a Population Mean: Normal (z) Statistic

6.3 Confidence Interval for a Population Mean: Student’s t-Statistic

6.4 Large-Sample Confidence Interval for a Population Proportion

6.5 Determining the Sample Size

6.6 Finite Population Correction for Simple Random Sampling (Optional)

6.7 Confidence Interval for a Population Variance (Optional)

            Inferences Based on a Single Sample: Estimation with Confidence Intervals

            Statistics in Action: Medicare Fraud Investigations

            Activity 6.1: Conducting a Pilot Study

            Using Technology: Confidence Intervals


7. Inferences Based on a Single Sample: Tests of Hypotheses

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Statistics for Business and Economics, CourseSmart eTextbook, 12th Edition
Format: Safari Book

$88.99 | ISBN-13: 978-0-321-82644-2