- Email: [email protected]
Quantitative techniques in a business context
BOOK
303
REVIEWS
and it is surprising that the authors did not give more attention to, for example, the revisions to SSAPs 9 and 13: from the few lines allotted, it is not even clear why the ASC should be bothering with a revision at all! Finally, while the authors give a chapter to special-purpose transactions, it is unfortunate (though not surprising, given the publication data) that they do not mention brands. Overall, then, Advanced Financial ilccounting is a useful and valuable book, but teachers adopting it will have to ensure that its omissions are adequately covered by other material. Comparing it with other textbooks aimed at the same market, I would rank this book best in terms of communication of materials and among the best in terms of coverage. I hope that the authors are already at work on a third edition. C. J. NAPIER L.S.E.
Ii. Slatcr & 1’. Ascroft QUANTITATIVE
TECHNIQUES
Chapman ei Hall (London,
IN
A BUSINESS
CONTEXT
1990). 391 pp. Al4.95
(pbk)
J. P. Dickinson STATISTICAL
ANALYSIS
IN
ACCOUNTING
Philip Allan (Hemel Hempstead,
AND
FINANCE
1990). 275 pp. A14.95 (pbk)
The central problems facing the author(s) of texts that apply quantitative analysis to a business or accounting context are what topics to include, and what degree of mathematical sophistication to assume in their readership. Although the subject matter of these two texts overlaps to a considerable extent, they take very different approaches to these central problems, with very different results in terms of accessibility. Quantitarive Trchniqurs in a Blrsiness Context (henceforth S&A) is aimed at undergraduates and is one of a series designed to ‘take a holistic view of Business Studies’. It assumes little prior knowledge and starts conventionally enough with sections covering clearly and succinctly the basics of descriptive statistics, algebra and calculus. The heart of the text is Part 4, and here the novelty of approach is that the authors first outline particular business problems and then derive the tools to solve them. Thus ‘Production and Control’ covers sampling, probability and hypothesis testing, ‘Marketing’ leads to questionnaire design, time series and regression forecasting, ‘Product Design and Development gives decision and network analysis. Other techniques fitted into these and further chapters include linear programming, the use of matrices, investment appraisal and non-parametric tests. The advantage of this approach is that it maintains student interest, the pages of statistical formulae arc diluted by more easily readable text and are seen to have a clear purpose. The result is a relatively painless and remarkably successful introduction: students will achieve an intuitive grasp of the techniques and may actually want to apply them when out in the big bad world. Moreover, the spirit of the text accords well with the ICAEW’s recent change to examination
304
BOOK
REVIEWS
of quantitative techniques within the rest of the syllabus, rather than as a separate topic. Of course there arc also disadvantages-it is more difficult to use the text for reference, for cxamplc, and some may criticise it as oversimplified and lacking in mathematical and intellectual rigour. But lists of further readings are given, and quite advanced topics such as heteroscendasticity and autocorrelation are touched on in context to alert students to possible difficulties. Of course it is easy to find areas whcrc one’s own taste would have given a little more detail (such as time series forecasting methods that allow for a trend), or a little less (perhaps graphical LP would have sufficed, without dual analysis). A solution in a future edition might be to have end of chapter notes. The presentation of the text is excellent, the writing is clear, key concepts, case studies and suggested solutions arc clearly diffcrcntiatcd, and there is a rcasonablc number of student rxcrcises. All in all, the more I looked at this book the more I liked it. Sfafistical Annlysis in Accountiq and Finawce takes a more traditional route. The author’s preface says that the book is for ‘the student, teacher, or practitioner of accounting who inevitably encounters statistical concepts in his or her work, and who needs an understanding of the concepts involved’. The implication is that the book is aimed at a more knowledgeable, and possibly more motivated audience than the S&A text. There is no coverage of descriptive statistics, and the techniques tend to bc discussed in the abstract, with applications mainly in the end of chapter exercises. The language is much more mathematical and intimidating. An example will illustrate the contrast with S&A. Describing multicollinearity S&A say this is ‘a situation where there are relationships, and high correlations, between the explanatory variables ,’ Dickinson says ‘this occurs if the assumption of linear independence between X,. X,, is violated’. Much of the ground covered is the same as S&A: probability, sampling and estimation, hypothesis testing, non-parametric statistics, regression and correlation, and time series. Treatment is to a higher statistical level than S&A, but not by much. A final chapter breaks new ground with multi-variate analysis giving brief introductions to discriminant, factor and cluster analysis. It is difficult to SW a niche for the Dickinson text. It is certainly not for the beginning student, although it might serve as a stepping stone towards a more advanced course such as one in econometrics. It might find a place on the reference shelves of the academic or practitioner with little statistical background, but I fear it is unlikely to fulfll the author’s implied aim of overcoming the fear of statistics as an abstruse and difficult subject. LYDIA THOMSON University of Aberdeen
303
REVIEWS
and it is surprising that the authors did not give more attention to, for example, the revisions to SSAPs 9 and 13: from the few lines allotted, it is not even clear why the ASC should be bothering with a revision at all! Finally, while the authors give a chapter to special-purpose transactions, it is unfortunate (though not surprising, given the publication data) that they do not mention brands. Overall, then, Advanced Financial ilccounting is a useful and valuable book, but teachers adopting it will have to ensure that its omissions are adequately covered by other material. Comparing it with other textbooks aimed at the same market, I would rank this book best in terms of communication of materials and among the best in terms of coverage. I hope that the authors are already at work on a third edition. C. J. NAPIER L.S.E.
Ii. Slatcr & 1’. Ascroft QUANTITATIVE
TECHNIQUES
Chapman ei Hall (London,
IN
A BUSINESS
CONTEXT
1990). 391 pp. Al4.95
(pbk)
J. P. Dickinson STATISTICAL
ANALYSIS
IN
ACCOUNTING
Philip Allan (Hemel Hempstead,
AND
FINANCE
1990). 275 pp. A14.95 (pbk)
The central problems facing the author(s) of texts that apply quantitative analysis to a business or accounting context are what topics to include, and what degree of mathematical sophistication to assume in their readership. Although the subject matter of these two texts overlaps to a considerable extent, they take very different approaches to these central problems, with very different results in terms of accessibility. Quantitarive Trchniqurs in a Blrsiness Context (henceforth S&A) is aimed at undergraduates and is one of a series designed to ‘take a holistic view of Business Studies’. It assumes little prior knowledge and starts conventionally enough with sections covering clearly and succinctly the basics of descriptive statistics, algebra and calculus. The heart of the text is Part 4, and here the novelty of approach is that the authors first outline particular business problems and then derive the tools to solve them. Thus ‘Production and Control’ covers sampling, probability and hypothesis testing, ‘Marketing’ leads to questionnaire design, time series and regression forecasting, ‘Product Design and Development gives decision and network analysis. Other techniques fitted into these and further chapters include linear programming, the use of matrices, investment appraisal and non-parametric tests. The advantage of this approach is that it maintains student interest, the pages of statistical formulae arc diluted by more easily readable text and are seen to have a clear purpose. The result is a relatively painless and remarkably successful introduction: students will achieve an intuitive grasp of the techniques and may actually want to apply them when out in the big bad world. Moreover, the spirit of the text accords well with the ICAEW’s recent change to examination
304
BOOK
REVIEWS
of quantitative techniques within the rest of the syllabus, rather than as a separate topic. Of course there arc also disadvantages-it is more difficult to use the text for reference, for cxamplc, and some may criticise it as oversimplified and lacking in mathematical and intellectual rigour. But lists of further readings are given, and quite advanced topics such as heteroscendasticity and autocorrelation are touched on in context to alert students to possible difficulties. Of course it is easy to find areas whcrc one’s own taste would have given a little more detail (such as time series forecasting methods that allow for a trend), or a little less (perhaps graphical LP would have sufficed, without dual analysis). A solution in a future edition might be to have end of chapter notes. The presentation of the text is excellent, the writing is clear, key concepts, case studies and suggested solutions arc clearly diffcrcntiatcd, and there is a rcasonablc number of student rxcrcises. All in all, the more I looked at this book the more I liked it. Sfafistical Annlysis in Accountiq and Finawce takes a more traditional route. The author’s preface says that the book is for ‘the student, teacher, or practitioner of accounting who inevitably encounters statistical concepts in his or her work, and who needs an understanding of the concepts involved’. The implication is that the book is aimed at a more knowledgeable, and possibly more motivated audience than the S&A text. There is no coverage of descriptive statistics, and the techniques tend to bc discussed in the abstract, with applications mainly in the end of chapter exercises. The language is much more mathematical and intimidating. An example will illustrate the contrast with S&A. Describing multicollinearity S&A say this is ‘a situation where there are relationships, and high correlations, between the explanatory variables ,’ Dickinson says ‘this occurs if the assumption of linear independence between X,. X,, is violated’. Much of the ground covered is the same as S&A: probability, sampling and estimation, hypothesis testing, non-parametric statistics, regression and correlation, and time series. Treatment is to a higher statistical level than S&A, but not by much. A final chapter breaks new ground with multi-variate analysis giving brief introductions to discriminant, factor and cluster analysis. It is difficult to SW a niche for the Dickinson text. It is certainly not for the beginning student, although it might serve as a stepping stone towards a more advanced course such as one in econometrics. It might find a place on the reference shelves of the academic or practitioner with little statistical background, but I fear it is unlikely to fulfll the author’s implied aim of overcoming the fear of statistics as an abstruse and difficult subject. LYDIA THOMSON University of Aberdeen