Test Bank for Statistics for Business and Economics 8th Edition by William Carlson, Betty Thorne, Paul Newbold ISBN 0132745658 9780132745659

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ISBN 10:   0132745658
ISBN 13: 978-0132745659
Author:    William Carlson, Betty Thorne, Paul Newbold

A classic text for accuracy and statistical precision.

Statistics for Business and Economics enables readers to conduct serious analysis of applied problems rather than running simple “canned” applications. This text is also at a mathematically higher level than most business statistics texts and provides readers with the knowledge they need to become stronger analysts for future managerial positions.

The eighth edition of this book has been revised and updated to provide readers with improved problem contexts for learning how statistical methods can improve their analysis and understanding of business and economics.

Additional business examples have been added in the chapter-opener and throughout the chapter

Statistics for Business and Economics 8th Table of contents:

CHAPTER 1 Describing Data: Graphical

1.1 Decision Making in an Uncertain Environment

1.2 Classification of Variables

1.3 Graphs to Describe Categorical Variables

1.4 Graphs to Describe Time-Series Data

1.5 Graphs to Describe Numerical Variables

1.6 Data Presentation Errors

CHAPTER 2 Describing Data: Numerical

2.1 Measures of Central Tendency and Location

2.2 Measures of Variability

2.3 Weighted Mean and Measures of Grouped Data

2.4 Measures of Relationships Between Variables

CHAPTER 3 Probability

3.1 Random Experiment, Outcomes, and Events

3.2 Probability and Its Postulates

3.3 Probability Rules

3.4 Bivariate Probabilities

3.5 Bayes’ Theorem

CHAPTER 4 Discrete Random Variables and Probability Distributions

4.1 Random Variables

4.2 Probability Distributions for Discrete Random Variables

4.3 Properties of Discrete Random Variables

4.4 Binomial Distribution

4.5 Poisson Distribution

4.6 Hypergeometric Distribution

4.7 Jointly Distributed Discrete Random Variables

CHAPTER 5 Continuous Random Variables and Probability Distributions

5.1 Continuous Random Variables

5.2 Expectations for Continuous Random Variables

5.3 The Normal Distribution

5.4 Normal Distribution Approximation for Binomial Distribution

5.5 The Exponential Distribution

5.6 Jointly Distributed Continuous Random Variables

CHAPTER 6 Sampling and Sampling Distributions

6.1 Sampling from a Population

6.2 Sampling Distributions of Sample Means

6.3 Sampling Distributions of Sample Proportions

6.4 Sampling Distributions of Sample Variances

CHAPTER 7 Estimation: Single Population

7.1 Properties of Point Estimators

7.2 Confidence Interval Estimation for the Mean of a Normal Distribution: Population Variance Known

7.3 Confidence Interval Estimation for the Mean of a Normal Distribution: Population Variance Unknow

7.4 Confidence Interval Estimation for Population Proportion (Large Samples)

7.5 Confidence Interval Estimation for the Variance of a Normal Distribution

7.6 Confidence Interval Estimation: Finite Populations

7.7 Sample-Size Determination: Large Populations

7.8 Sample-Size Determination: Finite Populations

8.1 Confidence Interval Estimation of the Difference Between Two Normal Population Means: Dependent

8.2 Confidence Interval Estimation of the Difference Between Two Normal Population Means: Independen

8.3 Confidence Interval Estimation of the Difference Between Two Population Proportions (Large Sampl

CHAPTER 9 Hypothesis Testing: Single Population

9.1 Concepts of Hypothesis Testing

9.2 Tests of the Mean of a Normal Distribution: Population Variance Known

9.3 Tests of the Mean of a Normal Distribution: Population Variance Unknown

9.4 Tests of the Population Proportion (Large Samples)

9.5 Assessing the Power of a Test

9.6 Tests of the Variance of a Normal Distribution

CHAPTER 10 Hypothesis Testing: Additional Topics

10.1 Tests of the Difference Between Two Normal Population Means: Dependent Samples

10.2 Tests of the Difference Between Two Normal Population Means: Independent Samples

10.3 Tests of the Difference Between Two Population Proportions (Large Samples)

10.4 Tests of the Equality of the Variances Between Two Normally Distributed Populations

10.5 Some Comments on Hypothesis Testing

CHAPTER 11 Simple Regression

11.1 Overview of Linear Models

11.2 Linear Regression Model

11.3 Least Squares Coefficient Estimators

11.4 The Explanatory Power of a Linear Regression Equation

11.5 Statistical Inference: Hypothesis Tests and Confidence Intervals

11.6 Prediction

11.7 Correlation Analysis

11.8 Beta Measure of Financial Risk

11.9 Graphical Analysis

CHAPTER 12 Multiple Regression

12.1 The Multiple Regression Model

12.2 Estimation of Coefficients

12.3 Explanatory Power of a Multiple Regression Equation

12.4 Confidence Intervals and Hypothesis Tests for Individual Regression Coefficients

12.5 Tests on Regression Coefficients

12.6 Prediction

12.7 Transformations for Nonlinear Regression Models

12.8 Dummy Variables for Regression Models

12.9 Multiple Regression Analysis Application Procedure

CHAPTER 13 Additional Topics in Regression Analysis

13.1 Model-Building Methodology

13.2 Dummy Variables and Experimental Design

13.3 Lagged Values of the Dependent Variable as Regressors

13.4 Specification Bias

13.5 Multicollinearity

13.6 Heteroscedasticity

13.7 Autocorrelated Errors

CHAPTER 14 Analysis of Categorical Data

14.1 Goodness-of-Fit Tests: Specified Probabilities

14.2 Goodness-of-Fit Tests: Population Parameters Unknown

14.3 Contingency Tables

14.4 Nonparametric Tests for Paired or Matched Samples

14.5 Nonparametric Tests for Independent Random Samples

14.6 Spearman Rank Correlation

14.7 A Nonparametric Test for Randomness

CHAPTER 15 Analysis of Variance

15.1 Comparison of Several Population Means

15.2 One-Way Analysis of Variance

15.3 The Kruskal-Wallis Test

15.4 Two-Way Analysis of Variance: One Observation per Cell, Randomized Blocks

15.5 Two-Way Analysis of Variance: More Than One Observation per Cell

CHAPTER 16 Time-Series Analysis and Forecasting

16.1 Components of a Time Series

16.2 Moving Averages

16.3 Exponential Smoothing

16.4 Autoregressive Models

16.5 Autoregressive Integrated Moving Average Models

CHAPTER17 Additional Topics in Sampling

17.1 Stratified Sampling

17.2 Other Sampling Methods

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