Statistics for Economics, Accounting and Business Studies, 7th edition

Published by Pearson (February 6, 2017) © 2017

  • Michael Barrow University of Sussex
Products list

Details

  • A print text

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, 7th Edition is a comprehensive introduction to the subject, offering a variety of statistical tools and techniques that will allow you to build your knowledge of Mathematics and Economics.

This latest edition includes updated content and recent examples using real-life data.

With a plethora of features and worked examples to support your understanding of the discipline, this must-read text will show you how to solve real-life economic problems and provide you with the resources to excel in your course.

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: S notation
    • Problems on S 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 c2 and F distributions
    • Learning outcomes
    • Introduction
    • The c2 distribution
    • The F distribution
    • Analysis of variance
    • Chapter summary
    • Key terms and concepts
    • Problems
    • Answers to Exercises
    • Appendix: Use of c2 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

Need help? Get in touch