Prentice Hall, 2006. (415 pages)
This text is aimed at students of economics and the closely related disciplines of accountancy and business, and provides examples and problems relevant to those subjects, using real data where possible. The book is at an elementary level and requires no prior knowledge of statistics, nor advanced mathematics. For those with a weak mathematical background and in need of some revision, some recommended texts are given at the end of this preface.
This is not a cookbook of statistical recipes; it covers all the relevant concepts so that an understanding of why a particular statistical test should be used is gained. These concepts are introduced naturally in the course of the text as they are required, rather than having sections to themselves. The book can form the basis of a one- or two-term course, depending upon the intensity of the teaching.
As well as explaining statistical concepts and methods, the different schools of thought about statistical methodology are discussed, giving the reader some insight into some of the debates that have taken place in the subject. The book uses the methods of classical statistical analysis, for which some justification is given in Chapter 5, as well as presenting criticisms which have been made of these methods.
Contents:
Descriptive statistics.
introduction.
Summarising data using graphical techniques.
Looking at cross-section data: wealth in the Uk in 2001.
Summarising data using numerical techniques.
The box and whiskers diagram.
Time-series data: investment expenditures 1970–2002.
Graphing bivariate data: the scatter diagram.
Data transformations.
Guidance to the student: how to measure your progress.
Summary.
Probability.
probability theory and statistical inference.
The definition of probability.
Probability theory: the building blocks.
Bayes’ theorem.
Decision analysis.
Summary.
Probability distributions.
introduction.
Random variables.
The Binomial distribution.
The Normal distribution.
The sample mean as a Normally distributed variable.
The relationship between the Binomial and Normal distributions.
The Poisson distribution.
Summary.
Estimation and confidence intervals.
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.
Summary.
Hypothesis testing.
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.
Discussion of hypothesis testing.
Summary.
The chi-Square and f distributions.
introduction.
The Chi-Square distribution.
The F distribution.
Analysis of variance.
Summary.
Correlation and Regression.
Introduction.
What determines the birth rate in developing countries?
Correlation.
Regression analysis.
Inference in the regression model.
Summary.
Multiple regression.
Introduction.
Principles of multiple regression.
What determines imports into the UK?
Finding the right model.
Summary.
Data collection and sampling methods.
Introduction.
Using secondary data sources.
Using electronic sources of data.
Collecting primary data.
The meaning of random sampling.
Calculating the required sample size.
Collecting the sample.
Case study: the Uk Expenditure and Food Survey.
Summary.
Index numbers.
Introduction.
A simple index number.
A price index with more than one commodity.
Using expenditures as weights.
Quantity and expenditure indices.
The Retail Price Index.
Inequality indices.
The Lorenz curve.
The Gini coefficient.
Concentration ratios.
Summary.
Important formulae used in this book.
This text is aimed at students of economics and the closely related disciplines of accountancy and business, and provides examples and problems relevant to those subjects, using real data where possible. The book is at an elementary level and requires no prior knowledge of statistics, nor advanced mathematics. For those with a weak mathematical background and in need of some revision, some recommended texts are given at the end of this preface.
This is not a cookbook of statistical recipes; it covers all the relevant concepts so that an understanding of why a particular statistical test should be used is gained. These concepts are introduced naturally in the course of the text as they are required, rather than having sections to themselves. The book can form the basis of a one- or two-term course, depending upon the intensity of the teaching.
As well as explaining statistical concepts and methods, the different schools of thought about statistical methodology are discussed, giving the reader some insight into some of the debates that have taken place in the subject. The book uses the methods of classical statistical analysis, for which some justification is given in Chapter 5, as well as presenting criticisms which have been made of these methods.
Contents:
Descriptive statistics.
introduction.
Summarising data using graphical techniques.
Looking at cross-section data: wealth in the Uk in 2001.
Summarising data using numerical techniques.
The box and whiskers diagram.
Time-series data: investment expenditures 1970–2002.
Graphing bivariate data: the scatter diagram.
Data transformations.
Guidance to the student: how to measure your progress.
Summary.
Probability.
probability theory and statistical inference.
The definition of probability.
Probability theory: the building blocks.
Bayes’ theorem.
Decision analysis.
Summary.
Probability distributions.
introduction.
Random variables.
The Binomial distribution.
The Normal distribution.
The sample mean as a Normally distributed variable.
The relationship between the Binomial and Normal distributions.
The Poisson distribution.
Summary.
Estimation and confidence intervals.
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.
Summary.
Hypothesis testing.
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.
Discussion of hypothesis testing.
Summary.
The chi-Square and f distributions.
introduction.
The Chi-Square distribution.
The F distribution.
Analysis of variance.
Summary.
Correlation and Regression.
Introduction.
What determines the birth rate in developing countries?
Correlation.
Regression analysis.
Inference in the regression model.
Summary.
Multiple regression.
Introduction.
Principles of multiple regression.
What determines imports into the UK?
Finding the right model.
Summary.
Data collection and sampling methods.
Introduction.
Using secondary data sources.
Using electronic sources of data.
Collecting primary data.
The meaning of random sampling.
Calculating the required sample size.
Collecting the sample.
Case study: the Uk Expenditure and Food Survey.
Summary.
Index numbers.
Introduction.
A simple index number.
A price index with more than one commodity.
Using expenditures as weights.
Quantity and expenditure indices.
The Retail Price Index.
Inequality indices.
The Lorenz curve.
The Gini coefficient.
Concentration ratios.
Summary.
Important formulae used in this book.