abc
abc
Suggested Reading List:(including a short critique of each text) Highly recommended / essential texts are marked with an * for level Cert and with two ** for level Int |
The first half of this book tends to focus upon how existing data might best be handled. Chapter 6 is useful in that it is concerned with the use of published ("official"!) statistics and this leads into the topics of Demography, Population dynamics and change. Later chapters give an insight into questionnaire design, controlled experiments and sampling schemes. Chapter 12 is covers the concept of time series and changes over time in a clear and lucid way.
The book is written in a formal style and may appear somewhat ‘dated’ by today’s standards.
Because this book assumes that the reader has a reasonable background in Mathematics, it is not suitable for the novice. However, Chapter 4 deals well with the subject of errors in raw data and encourages a thorough and systematic approach to data handling. Chapter 8 explains Hypothesis testing and Type 1 & 2 errors in a methodical way whilst Chapter 9 gives a solid explanation of Ranking and the tests associated with it. For the novice statistician, there are a number of books that are easier to follow.
Rather than being a book that is concerned with teaching Statistical procedures, this work concentrates on the crucial issue of how to go about setting up the investigation, selecting the right questions to ask. Initial Data Analysis (IDA) is crucial to using statistical methods effectively. An unusual feature of the book is to set exercises and then, rather than simply giving the answers, the author goes through the problem explaining how he would have tackled it. It is therefore a book about problem-solving rather than about learning to ‘do’ Statistics and in that sense, a useful read.
Although every effort is made to ‘lighten’ the subject; this is a very thorough book. The attempts at humour may not suit all, nevertheless many chapters are well worth reading in their entirety. Chapters 1,2, & 3discuss the nature of data, data measurement and sampling in a clear manner.
The book refrains from using too many formulae but rather emphasises the philosophy behind each test procedure. Chapters7 & 8 (frequency distributions, measuring variability and Normal Distributions) are explained in a comprehensive fashion. The later chapters of the book (dealing with comparisons and relationships) assume the use of a suitable computer software package.
The final chapter gives useful hints about writing up reports and making presentations to an audience.
The chapter on Samples and Populations is thorough but ponderous. There is an unorthodox terms used here; 'special batch' to describe the sampling distribution of the mean.
The basic principles of a t-test are neatly described. Unusually, the author chooses stem and leaf plots for the chapter on ANOVA and it is not particularly easy to follow. Similarly, the chapters on Correlation and Regression deal with the subjects in a cloudy way. The section ends with a neat working of Spearman's Rank Correlation. The final section discusses some deeper sampling concepts and issues that understandably relate to Archaeology specifically.
Elementary topics are discussed in a logical and workmanlike manner….Concepts, Descriptive Statistics, Sampling (particularly well defined), Comparisons (K-S, Mann-Whitney, Student’s ‘t’ and Chi etc ) Relationships and Trends. The inclusion of computer programmes (BASIC) for running on a BBC micro simply serve to illustrate how far we have travelled in the 17 years since the book was published. These pages have no relevance today
The main value of this book lies in Chapter 7 where spatial statistics, spatial patterns and nearest neighbour analysis are explained in a reasonably clear fashion. These techniques all have application
in Geography, Ecology and Archaeology when looking for patterning in the location of objects.
Although somewhat ‘dated’ in presentation, this book introduces the reader to the concept of classification, typologies and the very natural desire to ‘group’ things according to the characteristics that they have in common. Dendrograms and Linkage are explained in Chapter 3. The book becomes progressively more difficult and may only be of value to those who need to study Cluster Analysis for a dissertation.
In reality, this recent text is aimed at the ‘A’-Level Maths student. The material is set out in a pleasant and very readable format. The use of statistical calculators is encouraged.
Although eleven years old, this is a text aimed unashamedly at the practical archaeology student. It is true that the data set of 40 spearheads becomes, somewhat boring by the end of the book but by using this one data set throughout, it does serve to illustrate just how much valuable information can be retrieved from such a seemingly narrow source. Predictably, section 1 deal with the presentation of data in a conventional but readable fashion. In section 2 we are introduced to Probability, sampling theory, tests of Difference, tests of Distribution and finally non-parametric tests. Interestingly, section 3 gives an introduction to statistical computing but remember that the text is now 11 years old!
Overall, this is a textbook that all Archaeology undergraduates should have at hand.
The whole subject of Analysis of Variance is well covered (with a preliminary study in Chapter 16 of comparing two means). Principal Component Analysis is touched upon in the final chapter.
The language style adopted in this book is more ‘user-friendly’ than many others in this list.
The one thing that all modern Statistics textbooks seem to agree upon is that the average student does not like the subject! Therefore there are many attempts to find a 'winning formula' that will find favour with the student audience. This book is just one more attempt. The ring-binder format is intended to give the impression that this is a fieldwork book, at over 270 pages it patently is not!
The book also assumes from the outset that the audience is already conversant with computer -based statistical packages.
The material is otherwise dealt with in a competent manner beginning with 'cause and effect', types of data, Probability and Parametric distributions. ANOVA, Correlation and Regression are dealt with in some depth. An unusual chapter (highly specific to the Ecologist and Animal Behaviourist) deals with the analysis of circular data using the Honey Bee as the explanatory example.
This is a detailed, up to date and relevant text that can impart a great deal of information but there other current texts that can equally do the same thing and possibly better.
The book also offers online support.
This is an invaluable book but does not purport to be a textbook in the conventional sense. It is a handbook and meant to be used for ready reference purposes. The book is laid out in a clear and methodical way. Page 20 gives the layout to the book. It is at this point that the reader / researcher needs to be on firm ground because although each test is clearly defined, it is still imperative to understand which test is appropriate. Having decided upon the correct test; the book shows its true worth because one can follow the logic and the process through to the conclusions. Each test is also accompanied by a set of example data and this is used as a worked example. The book also contains the most complete set of statistical tables of any of the books reviewed here. There is that only one ANOVA test is included, 'G' tests are not included and occasionally tests are not listed by their normally recognised name. Nevertheless, allowing for these minor criticisms, this is an invaluable 'workshop' handbook.
Most Statistics text books state as their raison d’être that they were written "to fill a void", this one is no exception. In essence this simply means that the examples used are targeted towards the supposed inclinations of one or other group of students. Thus we have a perfectly usable text that covers Frequencies, Descriptive Statistics, Probability, Hypothesis testing, Simple linear regression and Correlation in a clear and logical manner. The research examples at the end of each chapter are very well done. The chapter on ANOVA is not easy to follow.
The overview would be that this book is set out in a straightforward, readable fashion.
"Mathematics is primarily the observation of patterns and relationships" and this is why it has relevance to the Archaeologist because this is what he has to do with the evidence of past lives found under the ground, so this text begins.
The need to ‘classify’ objects and to assess their frequency of occurrence is seen as a primary requirement in any archaeological investigation." Has this type of object been seen before? If so, where? and how often? "How common is X or how rare is something?"
Next, the book rapidly deals with Dendrograms and then RC dating procedures. Discriminant analysis is neatly covered with reference to artefact dispersion. Distribution mapping and distance analyses /settlement patterns are also well explained.
This is an excellent text that tries to explain how and why empirical methods are so useful in the Archaeological sciences.
This recent text quickly leaves descriptive statistics and probability behind. The chapters that follow; Hypothesis testing, ANOVA, Correlation, Regression are thorough rather than lucid. The material on Spatial patterns was also thorough but difficult to follow in places. However, the final chapter did give a valuable explanation of data reduction. Perhaps the main value of this text is the frequent reference to SPSS and how each procedure can be incorporated via this software. The Chapter on ANOVA exemplified this very well.
As the title suggests, the author has set out to make the learning process a little light-hearted. Beneath this deceptive exterior however, is a very comprehensive text that assumes little prior knowledge. There are repeated excursions into SPSS v.10 (there is even an SPSS tutorial as Appendix A and suggestions about useful Internet sites in Chapter 17).
The illustrations throughout are clear and helpful. Part 3 of the book concentrates on examining Hypothesis procedures, Probability and the Normal Distribution and Significance testing. The progression is conventional in that ANOVA.'s and non-parametric tests are as far as the book goes.
In terms of approachability to the subject, this book succeeds very well.
Archaeology is often concerned with deciphering patterns (of human activity for example). The introduction to this book explains why numerical analysis can be such a valuable tool in this respect.
After the preliminary chapters have dealt with descriptive statistics, there is a very good chapter on Correlation and regression and that leads neatly to multiple regression. Cluster analysis and the use of Dendrograms is handled in a thorough but somewhat clinical manner. There is also a comprehensive chapter on Principal Component Analysis. This book fits in well with the current topics contained in the core statistics teaching package.
By today's standards of textbooks, this text does not inspire. It is written in a dry and tedious manner.
However, as the title suggests, the material content is very important. Perhaps the main strength of the book is that specific Ordinal tests such as Wilcoxon's matched pairs, Mann-Whitney, K-S, Kruskal Wallis and Spearman's Rank Correlation are described in great detail and do constitute a large component of any research scientist' repertoire. Use this book if you are already competent in mathematics and wish to dig deeper.
This is an excellent book. Part one deals with Statistics Basics in a clear and engaging way. In fact, the author leads the reader through the conceptual ideas of statistical testing as an unfolding story. There are particularly well written chapters on undertaking surveys and experimental design. The explanation as to why we should wish to transform data (p86) is the clearest I have ever read (viz: to reduce the effects of extreme values in a data set).
Part 2 covers all the practical statistical tests that are likely to be encountered under normal circumstances commencing with t-tests, ANOVA, multivariate ANOVA, Chi squared, Non-parametric tests, PCA and finally, a very clear chapter explaining Cluster analysis. If you only intend to buy one textbook, then seriously consider this one.
It should be noted that this text was written primarily for the Behavioural Science undergraduate and so much emphasis is placed upon trying to get a 'feel' for the data to be used. However, such a skill would be just as valuable to an Environmental Science student. The design of experiments that will allow effective final analysis is a fundamental theme reinforced here and one that is often overlooked in many statistics textbooks.
This is a well-written text that deals with a complex topic in a structured and approachable way.
This is an unusual book in that it is written in a strange story-like form but it is included here because:
a) It is in the Bournemouth University library and b) It does have hidden depths.
For those students who have a genuine fear of working with numbers, this comfortable story text actually seems to work! The early chapters deal with Frequency Distributions, Dispersion and Mean Deviation. There follows a chapter covering Sampling, Bias and inferences that may be derived from a sample. There are also sections on Probability, Correlation and a final chapter covering Regression.
This is not a text that goes any further than Level one, or indeed covers all the material in level one but as a text to convey some of the elementary concepts in a gentle fashion, it has merit.
This is another excellent text, written in a clear and approachable style. The book begins as might be expected with two introductory chapters concerned with the "nature of data". Chapter 4 deals with the differences between samples and relates the examples to realistic environmental issues such as atmospheric pollution etc. Fully worked example calculations are followed at the end of each chapter by a wide range of environmentally orientated exercises (answers in Appendix E). The book goes no further than 2-way ANOVA's but this topic is covered extremely well. There is also a handy (and comprehensive) glossary of statistical terms and mathematical symbols.
It is unfortunate that this book does not touch upon PCA or Cluster analysis and it is surprising that a text written for environmental studies has nothing to say about population studies and demographics in general. Nevertheless, what it does cover, it executes exceptionally well and must therefore rank as a desirable text to own.
Explore the Electronic reading list also