# Essential Statistics for Economics, Business and Management

# Essential Statistics for Economics, Business and Management

ISBN: 978-0-470-98526-7 July 2011 674 Pages

**E-Book**

$62.50

## Description

*Essential Statistics for Economics, Business and Management*is aimed at introductory undergraduate courses and assumes no prior knowledge of statistics. It will also be highly relevant for the statistics component of courses in quantitative methods. The style of the text is similar to that of the highly successful

*Essential Mathematics for Economics and Business*by Teresa Bradley and Paul Patton, with many worked examples integrated throughout.

## Related Resources

### Student

**Introduction**1

**CHAPTER 1: Data Collection and its Graphical Presentation** 5

1.1 Introduction to statistics 6

1.2 Data collection: Samples, surveys and experiments 8

1.3 Some sources of statistical data 16

1.4 Sorting and classifying data 18

1.5 Charts: Bar charts, pie charts and plotting in Excel 23

1.6 Graphs: Histograms and Ogives. Graphs in Excel 42

1.7 Line and Lorenz graphs 52

1.8 Misleading graphs 59

**CHAPTER 2: Descriptive Statistics** 63

2.1 Summary statistics for raw data: Mean, quartiles and mode 64

2.2 Summary statistics for grouped data: Mean, quartiles and mode 72

2.3 Measures of dispersion for raw data. Variance, QD, IQR 85

2.4 Measures of dispersion for grouped data. Variance, QD, IQR 92

2.5 Use of calculator for descriptive statistics 94

2.6 Other descriptive statistics. CV, skewness and box plots 96

2.7 Descriptive statistics in Excel 101

**CHAPTER 3: Regression and Correlation: Introduction** 113

3.1 Introduction to regression: Scatter plots and lines 114

3.2 The least-squares line. Criteria and equation for the best fit line 118

3.3 Excel: XY (scatter) plots, the least-squares lines and formulae 127

3.4 Coefficient of determination and correlation 133

3.5 Rank correlation. Calculate and interpret rank correlation 144

3.6 Use the calculator for linear regression and correlation 146

3.7 Why bother with formulae? 154

**CHAPTER 4: Probability** 159

4.1 Introduction to probability 159

4.2 Multiplication and addition rules for probability 170

4.3 Joint, marginal and conditional probability 184

4.4 Bayes' Rule 192

**CHAPTER 5: Introduction to Probability Distributions** 205

5.1 Introduction to probability distributions and random variables 206

5.2 The Binomial probability distribution 212

5.3 The Poisson probability distribution 228

5.4 The Normal probability distribution 236

5.5 Expected values (mathematical expectation) 253

**CHAPTER 6: Sampling Distributions for Means and Proportions** 265

6.1 Statistical inference and the sampling distribution of the mean 265

6.2 Sampling distribution of proportions 275

6.3 Some desirable properties of estimators 282

**CHAPTER 7: Confidence Intervals for Means and Proportions** 287

7.1 Confidence intervals for the mean 287

7.2 Confidence intervals for proportions 297

7.3 The precision of confidence intervals for the mean 300

7.4 Confidence intervals for differences between means and proportions 304

**CHAPTER 8: Tests of Hypothesis for Means and Proportions** 319

8.1 Hypothesis tests for means 319

8.2 Hypothesis tests for proportions 334

8.3 Hypothesis tests for the difference between means and proportions 337

8.4 Minitab and Excel for confidence intervals and tests of hypothesis 349

**CHAPTER 9: Inference from Small Samples. Confidence Intervals and Tests of Hypothesis** 359

9.1 Inference from small samples: Normal populations, *s* known 360

9.2 The Student's *t* distribution 362

9.3 Inference from small samples: Normal populations, *s* NOT known 365

9.4 Difference between means. Small independent samples 370

9.5 *F*-test for equality of two variances 378

9.6 Difference between means, paired samples 382

**CHAPTER 10: Analysis of Variance** 393

10.1 The rationale behind one-way analysis of variance 393

10.2 One-way analysis of variance 397

10.3 Two-way ANOVA 419

10.4 ANOVA and design of experiment 430

10.5 Excel and Minitab for ANOVA 435

**CHAPTER 11: Chi-squared Tests** 453

11.1 Introduction 454

11.2 The *?*2 probability distribution 454

11.3 Contingency tables 455

11.4 *?*2 tests for independence (no association) 456

11.5 *?*2 test for homogeneous populations 464

11.6 *?*2 tests for the equality of several proportions 466

11.7 Goodness of fit tests 478

11.8 *?*2 tests in Minitab and Excel 490

**CHAPTER 12: Regression Analysis** 499

12.1 The simple linear regression model 499

12.2 Inference about the population slope (rate of change) 504

12.3 Confidence intervals and prediction intervals at *x* = *x*0 513

12.4 Checks on the model assumptions based on residuals plots 518

12.5 Regression analysis in Minitab and Excel 521

12.6 Multiple regression 534

**APPENDIX A: Technicalities and Conventions for Defining Class Intervals, Mid-Interval, Widths, Limits, Boundaries** 545

**APPENDIX B: Formulae for Calculating the Quartiles for Grouped Data** 547

**APPENDIX C: Outline of Derivation of Formulae (3.2) and (3.3) for the Slope and Intercept of the Least-Squares Line, Y = a + bX** 549

**APPENDIX D: Brief Review of the Mathematics for the Binomial** 551

**APPENDIX E: The Number e** 555

**APPENDIX F: Calculation of Mean and Variance of Proportions by Expected Values** 557

**APPENDIX G: Confidence Intervals for Means and Proportions** 559

**APPENDIX H: Degrees of Freedom** 561

**APPENDIX I: Notes on Summations and Double Summations** 563

**APPENDIX J: Expressing the Estimates of Variance as Sums of Squares Divided by Degrees of Freedom in Their Simplest Form** 567

**APPENDIX K: Sums of Squares for the One-Way ANOVA** 571

**APPENDIX L: Fitted Values and Residuals** 573

**APPENDIX M: Sums of Squares Identity for Two-Way ANOVA** 575

**Chapter Solutions** 577

**Tables** 637

Table 1 Cumulative Binomial Probability tables 637

Table 2 Cumulative Poisson Probabilities 639

Table 3 Normal probability Distribution 641

Table 4 Percentage point for the Normal probability distribution 642

Table 5 Percentage points of the Student’s *t*-distribution 643

Table 6 0.5% points of the *F*-distribution 644

Table 7 Percentage points for the Chi-squared distribution 648

Table 8 Table of random numbers 649

**Glossary** 651

**Index** 653

- Emphasis is placed on verbalizing concepts, problems and results of statistical analysis. This will help students learn how to start a problem, complete the calculations, and report the results in a way that makes sense to a non-statistician.
- Each concept is introduced with a brief but plausible explanation followed by Worked Examples. The Worked Examples will provide students with the necessary practice that they need in order to succeed at the subject.
- Emphasis is also placed on ‘learning through doing’ problems. Excel is used to encourage students in doing problems and to enhance understanding (with links to datasets online). Minitab printouts are also included in the text.
- Skills Development Exercises with brief solutions are included within the chapters, and Progress Exercises on theory and applications are provided at the end of each chapter. Solutions to all the Worked Examples and Progress Exercises are available as an appendix.
- Web-based supplementary materials will be provided for lecturers adopting the text, including additional exercises and solutions, excel datasets and exercises, PowerPoint slides with key formula, figures and tables.