ISE EBook Online Access for Statistical Techniques in Business and Economics.
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | eBook |
| Language: | English |
| Published: |
NY :
McGraw-Hill US Higher Ed ISE,
2017.
|
| Edition: | 17th ed. |
| Subjects: | |
| Online Access: | View fulltext via EzAccess |
Table of Contents:
- Cover
- Title Page
- Copyright Page
- Dedication
- A Note from the Authors
- Acknowledgments
- Brief Contents
- Contents
- 1 What is Statistics?
- Introduction
- Why Study Statistics?
- What is Meant by Statistics?
- Types of Statistics
- Descriptive Statistics
- Inferential Statistics
- Types of Variables
- Levels of Measurement
- Nominal-Level Data
- Ordinal-Level Data
- Interval-Level Data
- Ratio-Level Data
- EXERCISES
- Ethics and Statistics
- Basic Business Analytics
- Chapter Summary
- Chapter Exercises
- Data Analytics
- 2 Describing Data: FREQUENCY TABLES, FREQUENCY DISTRIBUTIONS, AND GRAPHIC PRESENTATION
- Introduction
- Constructing Frequency Tables
- Relative Class Frequencies
- Graphic Presentation of Qualitative Data
- EXERCISES
- Constructing Frequency Distributions
- Relative Frequency Distribution
- EXERCISES
- Graphic Presentation of a Distribution
- Histogram
- Frequency Polygon
- EXERCISES
- Cumulative Distributions
- EXERCISES
- Chapter Summary
- Chapter Exercises
- Data Analytics
- 3 Describing Data: NUMERICAL MEASURES
- Introduction
- Measures of Location
- The Population Mean
- The Sample Mean
- Properties of the Arithmetic Mean
- EXERCISES
- The Median
- The Mode
- EXERCISES
- The Relative Positions of the Mean, Median, and Mode
- EXERCISES
- Software Solution
- The Weighted Mean
- EXERCISES
- The Geometric Mean
- EXERCISES
- Why Study Dispersion?
- Range
- Variance
- EXERCISES
- Population Variance
- Population Standard Deviation
- EXERCISES
- Sample Variance and Standard Deviation
- Software Solution
- EXERCISES
- Interpretation and Uses of the Standard Deviation
- Chebyshev's Theorem
- The Empirical Rule
- EXERCISES
- The Mean and Standard Deviation of Grouped Data
- Arithmetic Mean of Grouped Data
- Standard Deviation of Grouped Data.
- EXERCISES
- Ethics and Reporting Results
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- 4 Describing Data: DISPLAYING AND EXPLORING DATA
- Introduction
- Dot Plots
- Stem-and-Leaf Displays
- EXERCISES
- Measures of Position
- Quartiles, Deciles, and Percentiles
- EXERCISES
- Box Plots
- EXERCISES
- Skewness
- EXERCISES
- Describing the Relationship between Two Variables
- Contingency Tables
- EXERCISES
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- Problems
- Cases
- Practice Test
- 5 A Survey of Probability Concepts
- Introduction
- What is a Probability?
- Approaches to Assigning Probabilities
- Classical Probability
- Empirical Probability
- Subjective Probability
- EXERCISES
- Rules of Addition for Computing Probabilities
- Special Rule of Addition
- Complement Rule
- The General Rule of Addition
- EXERCISES
- Rules of Multiplication to Calculate Probability
- Special Rule of Multiplication
- General Rule of Multiplication
- Contingency Tables
- Tree Diagrams
- EXERCISES
- Bayes' Theorem
- EXERCISES
- Principles of Counting
- The Multiplication Formula
- The Permutation Formula
- The Combination Formula
- EXERCISES
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- 6 Discrete Probability Distributions
- Introduction
- What is a Probability Distribution?
- Random Variables
- Discrete Random Variable
- Continuous Random Variable
- The Mean, Variance, and Standard Deviation of a Discrete Probability Distribution
- Mean
- Variance and Standard Deviation
- EXERCISES
- Binomial Probability Distribution
- How Is a Binomial Probability Computed?
- Binomial Probability Tables
- EXERCISES
- Cumulative Binomial Probability Distributions
- EXERCISES
- Hypergeometric Probability Distribution.
- EXERCISES
- Poisson Probability Distribution
- EXERCISES
- Chapter Summary
- Chapter Exercises
- Data Analytics
- 7 Continuous Probability Distributions
- Introduction
- The Family of Uniform Probability Distributions
- EXERCISES
- The Family of Normal Probability Distributions
- The Standard Normal Probability Distribution
- Applications of the Standard Normal Distribution
- The Empirical Rule
- EXERCISES
- Finding Areas under the Normal Curve
- EXERCISES
- EXERCISES
- EXERCISES
- The Normal Approximation to the Binomial
- Continuity Correction Factor
- How to Apply the Correction Factor
- EXERCISES
- The Family of Exponential Distributions
- EXERCISES
- Chapter Summary
- Chapter Exercises
- Data Analytics
- Problems
- Cases
- Practice Test
- 8 Sampling Methods and the Central Limit Theorem
- Introduction
- Sampling Methods
- Reasons to Sample
- Simple Random Sampling
- Systematic Random Sampling
- Stratified Random Sampling
- Cluster Sampling
- EXERCISES
- Sampling "Error
- Sampling Distribution of the Sample Mean
- EXERCISES
- The Central Limit Theorem
- EXERCISES
- Using the Sampling Distribution of the Sample Mean
- EXERCISES
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- 9 Estimation and Confidence Intervals
- Introduction
- Point Estimate for a Population Mean
- Confidence Intervals for a Population Mean
- Population Standard Deviation, Known σ
- A Computer Simulation
- EXERCISES
- Population Standard Deviation, σ Unknown
- EXERCISES
- A Confidence Interval for a Population Proportion
- EXERCISES
- Choosing an Appropriate Sample Size
- Sample Size to Estimate a Population Mean
- Sample Size to Estimate a Population Proportion
- EXERCISES
- Finite-Population Correction Factor
- EXERCISES
- Chapter Summary
- Chapter Exercises
- Data Analytics.
- Problems
- Cases
- Practice Test
- 10 One-Sample Tests of Hypothesis
- Introduction
- What is Hypothesis Testing?
- Six-Step Procedure for Testing a Hypothesis
- Step 1: State the Null Hypothesis (H0) and the Alternate Hypothesis (H1)
- Step 2: Select a Level of Significance
- Step 3: Select the Test Statistic
- Step 4: Formulate the Decision Rule
- Step 5: Make a Decision
- Step 6: Interpret the Result
- One-Tailed and Two-Tailed Hypothesis Tests
- Hypothesis Testing for a Population Mean: Known Population Standard Deviation
- A Two-Tailed Test
- A One-Tailed Test
- p-Value in Hypothesis Testing
- EXERCISES
- Hypothesis Testing for a Population Mean: Population Standard Deviation Unknown
- EXERCISES
- A Statistical Software Solution
- EXERCISES
- Type II Error
- EXERCISES
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- 11 Two-Sample Tests of Hypothesis
- Introduction
- Two-Sample Tests of Hypothesis: Independent Samples
- EXERCISES
- Comparing Population Means with Unknown Population Standard Deviations
- Two-Sample Pooled Test
- EXERCISES
- Unequal Population Standard Deviations
- EXERCISES
- Two-Sample Tests of Hypothesis: Dependent Samples
- Comparing Dependent and Independent Samples
- EXERCISES
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- 12 Analysis of Variance
- Introduction
- Comparing Two Population Variances
- The F Distribution
- Testing a Hypothesis of Equal Population Variances
- EXERCISES
- ANOVA: Analysis of Variance
- ANOVA Assumptions
- The ANOVA Test
- EXERCISES
- Inferences about Pairs of Treatment Means
- EXERCISES
- Two-Way Analysis of Variance
- EXERCISES
- Two-Way ANOVA with Interaction
- Interaction Plots
- Testing for Interaction
- Hypothesis Tests for Interaction
- EXERCISES
- Chapter Summary.
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- Problems
- Cases
- Practice Test
- 13 Correlation and Linear Regression
- Introduction
- What is Correlation Analysis?
- The Correlation Coefficient
- EXERCISES
- Testing the Significance of the Correlation Coefficient
- EXERCISES
- Regression Analysis
- Least Squares Principle
- Drawing the Regression Line
- EXERCISES
- Testing the Significance of the Slope
- EXERCISES
- Evaluating a Regression Equation's Ability to Predict
- The Standard Error of Estimate
- The Coefficient of Determination
- EXERCISES
- Relationships among the Correlation Coefficient, the Coefficient of Determination, and the Standard Error of Estimate
- EXERCISES
- Interval Estimates of Prediction
- Assumptions Underlying Linear Regression
- Constructing Confidence and Prediction Intervals
- EXERCISES
- Transforming Data
- EXERCISES
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- 14 Multiple Regression Analysis
- Introduction
- Multiple Regression Analysis
- EXERCISES
- Evaluating a Multiple Regression Equation
- The ANOVA Table
- Multiple Standard Error of Estimate
- Coefficient of Multiple Determination
- Adjusted Coefficient of Determination
- EXERCISES
- Inferences in Multiple Linear Regression
- Global Test: Testing the Multiple Regression Model
- Evaluating Individual Regression Coefficients
- EXERCISES
- Evaluating the Assumptions of Multiple Regression
- Linear Relationship
- Variation in Residuals Same for Large and Small y Values
- Distribution of Residuals
- Multicollinearity
- Independent Observations
- Qualitative Independent Variables
- Regression Models with Interaction
- Stepwise Regression
- EXERCISES
- Review of Multiple Regression
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- Problems.
- Cases.