Super Crunchers – Ayres (2007) – 1/2

With the Triumph of Numbers, I read and wrote about the power of using numbers, and how the observation of empirical regularities led to the basic knowledge on how to use such numbers. Already in the triumph of numbers, it was indicated how valuable (numerical) data were regarded to be, for instance by the recollection how the first censuses were regarded as state secrets, because the information could be used to make assertions about the military strength of (rival) nations.

Unfortunately, I.B. Cohen’s Triumph of Numbers ended quite abruptly with a description of Florence Nightingale. It felt unfinished. But the use of numbers has evolved since, and quite substantially so.

How much our use of numerical data has evolved, and to what extent is has invaded our daily lives (without many of us knowing it!), is convincingly described by Ian Ayers, in his magnificent book ‘Super Crunchers’ (2007).

Companies know more and more (and more!) about you: you buy products online, you speak with the customer relations department (with a person behind a computer), you gain discounts with customer cards, and of course you are careful to make sure you receive you frequent flyer miles. Right? If not, you may have bought it all using a credit card, the transactions of which are stored anyway. … Continue Reading

Statistical Tools – Te Grotenhuis and Van der Weegen (2009)

How does one teach statistics? Is it more important to start with mathematical thoroughness, or to help students to gain a conceptual understanding first? Few give a comprehensive introduction to statistics for those without the otherwise indispensable mathematical background. Manfred te Grotenhuis and Theo van der Weegen recently published an introductory book on statistics, explaining statistical concepts using words and graphs, rather than formulas.

Less than a year ago, I wrote these exact words. I then discussed the publication of a Dutch book on statistics, to which I provided minor assistance. Now, I repeat these words to introduce the Enligsh translation of this conceptual introduction to statistics, called Statistical Tools. Again, I contributed to this publication, this time by providing a first, rough, translation from Dutch to English. Let me repeat below what I wrote before on this blog, for of course this still holds relevance for the translation to English:

With the focus on practical application rather than statistical theory, the first chapter starts explaining the goal of inferential statistics, meanwhile introducing the concepts of measurement and variables. Considerable attention is paid to the importance of high quality data to perform your analyses on. The second chapter … Continue Reading

The Triumph of Numbers – Cohen (2005)

My new job involves working with numbers. A lot. So, I started reading about using numbers, and I very much enjoyed ‘The Triumph of Numbers’ by I.B. Cohen (2005). This book gives an historical account not only of how numbers were used in different times, but also of ‘how counting shaped modern life’.

The books starts out by illustrating the power of numbers. Just by using very simple calculations, Cohen quickly arrives at the conclusion that the building of the ancient pyramids involved placing one giant block of stone in the structure, every two minutes. Since the weight of such stones is enormous, this required quite advanced techniques to achieve. Knowing the vast size of such an operation, this helps us to gain an understanding in how the Egyptians may have done it, and the level of technology available to them.

For long, people have been fascinated by numbers. Cohen’s description of the history of using numbers therefore starts with numerology. The reader is treated with lovely exercises is numerology: it is quite amazing how we can prove about anything, simply by reordering numbers that somehow correspond to letters. If only there was an empirical basis for such magic.

Off to more serious applications of numbers (by today’s standards), Cohen locates the proper start of using numbers in Hutcheson’s Moral Arithmetic. Hutcheson used formulae (and which are based on numbers) to make his claims about morality. Here, numbers were only used to illustrate a claim, but not much later people started to relate such numbers to observable phenomena. An example of this Benjamin Franklin, who used his mathematical genius to find arguments based on numbers for his political claims regarding the safety of inoculation against smallpox. He used numbers to show it was safe to have your children inoculated.
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Book: A conceptual introduction to statistics

How does one teach statistics? Is it more important to start with mathematical thoroughness, or to help students to gain a conceptual understanding first? There’s something to say about both, depending on the setting you’re in, but fact is that most books on statistics (even the introductory ones) rapidly delve into the mathematical depths of inferential statistics. Few give a comprehensive introduction to statistics for those without the otherwise indispensable mathematical background. Manfred te Grotenhuis and Theo van der Weegen recently published an introductory book on statistics called “Statistics as a Tool” (Statistiek als Hulpmiddel, in Dutch), explaining statistical concepts using words and graphs, rather than formulas.

… Continue Reading

R-Sessions 25: Book – Mixed Effects Models in S and S-PLUS (Pinheiro & Bates, 2000)

Despite the reference to S and S-PLUS in the title of this book, it offers an excellent guide for the nlme-package in R-Project. Reason for this is the close resemblance between R and S. The nlme-package, available in R-Project for estimation of both linear and non-linear multilevel models, is written and maintained by the authors of this book.
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R-Sessions 24: Book: An R and S-PLUS Companion to Applied Regression (John Fox, 2002)

For those who have some theoretical knowledge on statistics and regression techniques, and who want to learn to use R-Project to analyze some data, John Fox wrote just the book.

The introductory chapter shows the most basic aspects of R-Project. Halfway this chapter the reader finds himself analyzing real data using regression techniques. The following chapters introduce the reader to other aspects of the analytical process: reading data into your statistical program, exploring the data and performing some bivariate tests. Then, three full chapters are devoted to regression techniques. While working on practical examples, the reader is introduced to more fundamental aspects of the R-Project software where needed.
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R-Sessions 23: Book: Data Analysis Using Regression and Multilevel/Hierarchical Models — Gelman & Hill (2007)

Data Analysis Using Regression and Multilevel/Hierarchical Models

Andrew Gelman is known for his expertise on Bayesian statistics. Based on that knowledge he wrote a book in multilevel regression using R and WINbugs. This book aims to be a thorough description of (multilevel) regression techniques, implementation of these techniques in R and bugs, and a guide on interpreting the results of your analyses. Shortly put, the books excels on all three subjects.
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R-Sessions 22: Book: Introductory Statistics with R — Peter Dalgaard (2002)

Introductory Statistics with R

Peter Dalgaard is associate professor at the Department of Biostatistics at the University of Copenhagen in Denmark, and a member of the R-Project Core Development team. Also, he is an active participating and respected member of the R-help mailing-list. Based on these experiences, he set to write an introductory book on statistics and R.

The book start with relatively simple topics, easily working toward more complex statistical problems. Central techniques that are covered are analysis of variance and regression. Starting with bivariate analyses, multivariate analyses of both types are discussed to a high extent. Several types of linear (regression) models are introduced, covering polynomial regression, regression without an intercept, interactional model, two-way ANOVA with replication, and ANCOVA. A separate chapter focusses on logistic regression. Moreover, in many ways the equivalence or parallels of regression and ANOVA are discussed. Thereby, a greater understanding of the (differences between) techniques is stimulated.
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Collective curiosity?

Those of you who have ever attended a ‘Fête Nos’, a typical Brêton festival-type of gathering with music and people dancing, may immediately understand what I’m going to write about. All the others who have attended another gathering of a large number of people will also be completely familiar with my revived curiosity in a specific subject: The collectivity of human behavior and its occurrence in large masses of people.

Every time the music starts at a crowded ‘Fête Nos’, something peculiar happens: within seconds the mass of people all talking to each other and walking seemingly random suddenly are dancing all together in familiar patterns. This pattern is way too complex to be laid upon all those people: it must, somehow, emerge from the individual moves these people make. Interesting and intriguing, don’t you think?

Even before I started studying sociology I had read `Critical Mass’ (2004) by Philip Ball. I loved this overview of popular science and still do, but somehow it had moved to the back of my memory. I remembered the actor- or boid-based simulations, but I did not really understand how this could be related to the theory-driven sociology that I was studying. I recognized the possibilities offered by the described simulation techniques, but saw them as theories, rather than empirical tests: we can easily make assumptions about behavior and simulate the consequences of that, but then we still don’t know if these assumed behaviors indeed exist and happen in reality.
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