Increase your confidence in Statistics and build up your skills for excellence with this reader-friendly guide to the field.

Statistics for Economics, Accounting, and Business Studies, 7^th Edition by Michael Barrow is a user-friendly, comprehensive introduction to the subject, offering a variety of statistical tools and techniques that will help you build your skills and knowledge in Mathematics and Economics.

Ideal for students of economics and the closely related disciplines of accountancy, finance, and business, this is an easy-to-follow text that does not require prior knowledge of Statistics. The book guides you through the essential principles of the field and provides a thorough analysis of statistical concepts and methods.

This latest edition will offer you new and updated content regarding topics, such as statistical reports, graphs, and hypothesis testing. The text also includes updates to demonstrate recent examples and real-life data.

With a plethora of features to support, practice, and test your understanding of the discipline, this essential learning resource will help you solve real-life economic problems, providing an insight into the relationship between statistical techniques and relevant concepts.

Michael Barrow is a Senior Lecturer in Economics at the University of Sussex. He has acted as a consultant for major, industrial, commercial and government bodies

Preface to the fourth edition

Introduction

1 Descriptive statistics

Learning outcomes

Introduction

Summarising data using graphical techniques

Looking at cross-section data: wealth in the UK in 2005

Summarising data using numerical techniques

The box and whiskers diagram

Time-series data: investment expenditures 1977–2009

Graphing bivariate data: the scatter diagram

Data transformations

The information and data explosion

Writing statistical reports

Guidance to the student: how to measure your progress

Chapter summary

Key terms and concepts

Problems

Answers to Exercises

Appendix 1A:  notation

Problems on  notation

Appendix 1B: E and V operators

Appendix 1C: Using logarithms

Problems on logarithms

References

2 Probability

Learning outcomes

Probability theory and statistical inference

The definition of probability

Probability theory: the building blocks

Bayes’ theorem

Decision analysis

Chapter summary

Key terms and concepts

Problems

Answers to Exercises

3 Probability distributions

Learning outcomes

Introduction

Random variables

The Binomial distribution

The Normal distribution

The distribution of the sample mean

The relationship between the Binomial and Normal distributions

The Poisson distribution

Chapter summary

Key terms and concepts

Problems

Answers to Exercises

4 Estimation and confidence intervals

Learning outcomes

Introduction

Point and interval estimation

Rules and criteria for finding estimates

Estimation with large samples

Precisely what is a confidence interval?

Estimation with small samples: the t distribution

Chapter summary

Key terms and concepts

Problems

Answers to Exercises

Appendix: Derivations of sampling distributions

5 Hypothesis testing

Learning outcomes

Introduction

The concepts of hypothesis testing

The Prob-value approach

Significance, effect size and power

Further hypothesis tests

Hypothesis tests with small samples

Are the test procedures valid?

Hypothesis tests and confidence intervals

Independent and dependent samples

Issues with hypothesis testing

Chapter summary

Key terms and concepts

Problems

Answers to Exercises

6 The 2 and F distributions

Learning outcomes

Introduction

The 2 distribution

The F distribution

Analysis of variance

Chapter summary

Key terms and concepts

Problems

Answers to Exercises

Appendix: Use of 2 and F distribution tables

7 Correlation and regression

Learning outcomes

Introduction

What determines the birth rate in developing countries?

Correlation

Regression analysis

Inference in the regression model

Chapter summary

Key terms and concepts

Problems

Answers to Exercises

References

8 Multiple regression

Learning outcomes

Introduction

Principles of multiple regression

What determines imports into the UK?

Finding the right model

Chapter summary

Key terms and concepts

Problems

Answers to Exercises

References

9 Data collection and sampling methods

Learning outcomes

Introduction

Using secondary data sources

Collecting primary data

Random sampling

Calculating the required sample size

Collecting the sample

Case study: the UK Living Costs and Food Survey

Chapter summary

Key terms and concepts

Problems

References

10 Index numbers

Learning outcomes

Introduction

A simple index number

A price index with more than one commodity

Using expenditures as weights

Quantity and expenditure indices

The Consumer Price Index

Discounting and present values

Inequality indices

The Lorenz curve

The Gini coefficient

Concentration ratios

Chapter summary

Key terms and concepts

Problems

Answers to Exercises

Appendix: deriving the expenditure share form of the

Laspeyres price index

References

11 Seasonal adjustment of time series data

Learning outcomes

Introduction

The components of a time series

Isolating the trend

Isolating seasonal factors

Seasonal adjustment

An alternative method for finding the trend

Forecasting

Further issues

Chapter summary

Key terms and concepts

Problems

Answers to Exercises

List of important formulae

Appendix: Tables

Answers to problems

Index

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