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Reviews Written by G.X. Larson (Southeastern Michigan)

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1 of 1 people found the following review helpful
Short and to the point: a good guide to Python, July 24, 2014
First, a few things that this book isn't: it isn't an encyclopedic or incredibly comprehensive guide to the Python programming language. It also isn't an introduction to computer programming or people who have never programmed before. Instead, this book is a brief introduction to the Python language focusing on basic features common to all languages (I/O, string manipulation, data structures, etc.). Readers who have been programming for a long time will find this book useful since it provides a quick and easy introduction to Python syntax.
Programmers with less experience will also do well to read this book as it provides concrete examples of many basic (yet essential) programming features and concepts. The best part about this book is that it is short and to the point: the reader will not get lost in pages and pages of needless detail; it is truly a "quick start" guide to Python. Again, if you are looking for a tome on the inner workings of Python, then look elsewhere. I also don't recommend this book for absolute beginners (unless they package it with something that is more of an introduction to programming). I think this book is a great introduction to Python.









Good Overview, July 18, 2014
This past decade has witnessed the rise of phrases such as "predictive analytics", "sabermetrics" and "big data" in everyday conversation and in the media. No doubt these phrases reached the public with the success of films like Moneyball, the success of Facebook, and the success of people like Nate Silver. Indeed, I think this past decade has given rise to a new recreation: recreational statistics. This book is an excellent overview of the subject for those wanting an introduction to predicting presidential elections using statistics. This slim book introduces the reader to several ways that one can predict an American presidential election. Amazon provides no "look inside" preview for this book, so I've provided the table of contents below:
1. Trial Heat Polls 2. Bellwethers 3. Presidential Approval Ratings 4. Other Public OpinionBased Techniques 5. JudgmentBased Forecasting Techniques 6. Cycles in Presidential Elections 7. The Nomination Process and Campaigns 8. Performance of the Economy 9 Putting it All Together: Multivariate Forecasting Models
Each chapter discusses a model and provides empirical results. Aside from models similar to the one described in chapter 8, my personal favorite is one first described by political scientist Alan Abramowitz and discussed in chapter 6. This model shows that it is possible to put forth a reasonably accurate prediction of which party will win the presidential election four years prior to the election taking place. That is, without knowing which candidates will run in the election, and without knowing the state of the economy, etc.
This is the only book I know of to provide a clear introduction to predicting American presidential elections. My one major complaint is that little to no data are provided for each of the models discussed in the book.









2 of 5 people found the following review helpful
Solid Introduction to Discrete Mathematics, July 29, 2013
Most will use this book in a college class called "Introduction to Discrete Mathematics" or something similar with the word "discrete" in its title. For many it will be a first introduction to mathematical proofs. Appropriately Rosen's textbook begins with the basics of logic and proof writing, moves on to topics that are important in all of mathematics, such as sets and functions, and then continues on to various other topics in discrete math (such as discrete probability, graphs, and trees). Definitions and theorems are nicely highlighted. There are many problems of varying difficulty at the end of each section, some drill the fundamentals and others much more difficult. Answers to odd problems are included in the back of the book. Amazon provides no "look inside" preview for this textbook, so I've provided the table of contents below:
1. The Foundations: Logic and Proof 2. Basic Structures: Sets, Functions, Sequences, Sums, and Matrices 3. Algorithms 4. Number Theory and Cryptography 5. Induction and Recursion 6. Counting 7. Discrete Probability 8. Advanced Counting Techniques 9. Relations 10. Graphs 11. Trees 12. Boolean Algebra 13. Modeling Computation
Part of the difficulty associated with this book is that an "introduction to discrete mathematics" is by nature a smorgasbord of different subjects: probability, algorithm analysis, number theory, graph theory, and combinatorics to name several. The goal for an appropriate textbook is to introduce each subject thoroughly yet within a certain number of pages. I think Rosen has done a fine job, and although the book is around 1000 pages long and weighs a ton, I felt that as a student I was introduced to each subject thoroughly enough.









A Medieval Mystery, July 29, 2013
This novel is one of a kind. Sure, there exists the genre of historical fiction, but Umberto Eco actually immerses the reader into a 14th century Italian monastery with his prose, which is styled to imitate the language of the time (or what comes to us today via translation). Countless times I felt like I was reading something akin to "The Life of St. Anthony", or a work by Aristotle or Francis Bacon. However, due to this fact the book can be challenging to read. But if you are like me and enjoy old works of philosophy or history then you will enjoy being immersed into this tale. Indeed, Eco acknowledges in the Postscript that the stylized prose is like the suspenseful music that plays during a thriller movie.
The plot is a standard one: a whodunnit murder mystery set inside the walls of a medieval monastery. The main characters are a masterandapprentice duo, with the master being William of Baskerville (who is very much modeled after a certain famous detective in English literature), and the apprentice and narrator being Adso of Melk, who is different enough from the master to provide Eco with a vehicle to explore different subplots seemingly unrelated to the main mystery. But in addition to the quite standard whodunnit there are many interesting encounters between the main characters and the various monks of the monastery. There are quite a few intellectual debates between William and others, all of which are like reading actual transcripts of debates by real medieval theologians. But reader beware: although it is tempting to skim through these encounters and debates (which can be viewed as subplots) in order to get back to the main plot (the murder mystery), I assure you that carefully reading the intellectual discussions will make the climax all the more worthwhile and enjoyable. And what a climax it is!









A good choice for the engineering or science student, January 8, 2013
This textbook is a good choice for a class on introductory differential equations for students of science and engineering. That is to say that it focuses on the applications and not so much on the theory. The book even includes some Matlab, Maple, and Mathematica code. The book One of the virtues of this book is the number (a lot) of practice problems attached to each section. Also, the back of the book includes solutions to many even numbered problems (and odd problems, too). Here is a reproduction of the table of contents for this book (since there is no "look inside" feature):
1. First Order Differential Equations 2. Mathematical Models and Numerical Methods 3. Linear Equations of Higher Order 4. Introduction to Systems of Differential Equations 5. Linear Systems of Differential Equations 6. Nonlinear Systems and Phenomena 7. Laplace Transform Methods
One of my few complaints is that some of the material is introduced in strange places (such as in a practice problem), and sometimes it was frustrating when a concept was introduced only with respect to its application (one instance was second order systems, which were tied to mechanical systems). Sometimes it would have been nice to learn the ins and outs of a concept and then move on to its applications. But all in all I think that the student looking for an applied approach to differential equations will do well to give this textbook a look.









9 of 10 people found the following review helpful
Solid Introduction, January 8, 2013
In my opinion the reviews on this site do not reflect the true rating of this book. I can't compare this book to other linear algebra textbooks but I can say that I am glad that the linear algebra course that I took had this as the assigned book. Theorems, definitions, and other key points are expressed clearly and even vividly (all theorems and definitions are enclosed in a colored box so that the reader can easily find them). The pictures/graphics are also an excellent feature to Lay's book, and I know that I benefited from being able to visualize certain concepts. Here is a reproduction of the table of contents (since amazon doesn't have a "look inside" for this book; a more detailed table of contents can be found at the publisher's website):
1. Linear Equations in Linear Algebra 2. Matrix Algebra 3. Determinants 4. Vector Spaces 5. Eigenvalues and Eigenvectors 6. Orthogonality and Least Squares 7. Symmetric Matrices and Quadratic Forms 8. The Geometry of Vector Spaces
Chapter 8 is a new addition, and was not included in the 3rd edition (we didn't cover it in my class, but I remember seeing stuff like Bezier curves in that chapter). Speaking as a student, I liked how this textbook started off slow and gradually built up towards more complex topics. That's not to say that the initial chapters are fluff; they were covered in a rigorous manner which allows the student to build on each new logical concept from the previous ones. I also liked the many applied examples that Lay included: even if you never use linear algebra again (but chances are that you will, if you're taking linear algebra in the first place) you will appreciate applications such as Markov chains and linear regression. I also appreciated the proofs that Lay included (almost all of the theorems are proved), as well as the proof problems included at the end of each section. Linear algebra is unlike any other math class if you have only ever done the standard calculus sequence. But with Lay's book this shouldn't be a problem.









1 of 1 people found the following review helpful
The merits and limits of rational choice theory, August 22, 2012
This is a great introduction to rational choice theory as it pertains to voting in elections. Since I have started reading books about elections I have been asking people why they vote. Many of my friends do not vote at all (I am in my early twenties, so this fact should not be a surprise). Usually the reason for this is apathy: they don't really think there's a significance between the two candidates (USA) and don't really think their votes will make an impact. On the other hand, the reasons my close family gives for voting, at least this year (2012) is that they don't want to see the Republicans win. When asked if they have given thought to the fact that their votes are negligible in so far as the probability is low that their votes will decide the (statewide) election, I usually hear something along the lines of "but enough people vote such that the aggregate effect does determine the outcome". If you have ever thought about these issues, then Blais's "To Vote or Not to Vote?" is an excellent overview of a famous theory of voting: rational choice theory.
Recall my friends who do not vote: for them, the benefits to voting are small, if any. For my family, the potential benefit of voting is enormous: I will simply say that they do not typically like Republican presidents. Under standard rational choice theory however, those who vote are irrational. This can be shown by the equation, R = PB  C, where R is utility gained through the action of voting, PB is the product of the probability that one's vote will be decisive times the benefit the voter will receive if her preferred candidate wins, and C is the cost of voting. Usually P is microscopic, such that even if C is small, the difference, R, will be negative. Hence the paradox of voting.
Theorists have added many qualifications to the rational choice model in attempts to explain why people vote. A "D" term, for example, has been added by some (Riker and Ordeshook) to account for a voter's notion of duty, while others (Ferejohn and Fiorina) have argued that voters operate under the guise of minimax regretmeaning that if a nonvoting citizen's preferred candidate were to lose by one vote, then that nonvoting citizen would feel horrible (at a magnitude much greater than if her candidate were to win: hence the citizen votes to ensure that she will not experience that horrible feeling of guilt). One of my favorite explanations for the paradox is that voting at the state or national level is a lowstake decision, so voters can afford to act "irrationally". I also have a pet theory that says that engaged citizens spend time to follow the news and campaigns; this time is an investment that, according to rational choice, will see very little return ( a low or negative R). A citizen will vote in order to tell himself that that time was not wasted. (Yes... very tautologous.) In this book, Blais seeks to investigate if rational choice theory has any semblance of reality, and where it does now, investigate the alternatives.
The book is well worth the read. A few highlights: Blais finds that about half of the electorate (his surveys are taken in Canada) overestimates the probability that their vote will be decisive. However, a significant number of voters have a profound sense of duty. Many say that they would vote even if they knew their vote would not have an impact on the outcome of an election; instead, their vote would be cast as a symbolic action to uphold the principles of democracy. Blais finds that for the rational choice equation, P and B are not multiplicative, but are additive, which helps explain why one would vote even if P were very small. When all is said and done, Blais does not argue that rational choice theory is inappropriate. Like the subtitle says, he finds both merits and limits to the theory.
I end with this quote from Blais, in the hopes that the reader of this review will be moved to vote in the future: "Should not the rational individual reason that whether she votes or not will not salvage or jeopardize democracy in her country? My only response is that, like many of my fellow citizens, I feel that I must act in accordance with the principles I believe in. As I think of myself as a democrat, it would be incongruous not to vote. I vote, then, because I want to be consistent with my principles. Yes, I would feel somewhat guilty not to vote."









Do campaigns matter?, August 22, 2012
If you know anything about serious election forecasting (not the type done by pundits on television) then you know that they are easily predicted. In fact, anyone with access to Microsoft Excel can create their own reasonably good regression model based on as little as four variables. You could even generate a regression model with pencil and paper (and patience) using only (matrix) arithmetic. Economist Ray Fair (author of Predicting Presidential Elections and Other Things) has a wellknown model that predicts the proportion of the twoparty vote that the incumbent party will receive in an election based on three variables: 1) growth rate of real per capita GDP in the first 3 quarters of an election year; 2) growth rate of the GDP deflator; 3) number of quarters in the first 15 quarters of the incumbent party's term in which the growth rate of real per capita GDP is greater than 3.2 percent at an annual rate. Clearly Fair's hypothesis is that economic conditions shape election outcomes; or, "it's the economy, stupid". It goes without saying that his model can accurately predict the winner of an election even before the candidates have been selected. Other models may incorporate party strength, perceived economic conditions (subjective metrics of the economy, such as consumer sentiment, rather than objective measures used by Fair), party tenure (duration that an incumbent party has held the presidency), and actual measures of candidate popularity such as trialheat poll data. Many models accurately predict the winner months in advance, which leads us to the question: if American presidential elections are so predictable, do campaigns matter? The answer is yes and no. First, it is important to understand Holbrook's notion of equilibrium. Holbrook first uses a linear model to predict the winner of a presidential election based on data from no later than the month of May. His regression uses three variables: popularity (basically a preview of the November election), aggregate personal finances, and party tenure. This model is generally very accurate, accounting for roughly 84 percent of the data set's variability. The proportion of total vote a candidate receives as predicted by the model is that candidate's equilibrium. Since Holbrook's vote share regression is so indicative of the actual election outcome (and it is important to remember that it is based on data from no later than May of each election year) it is fairly obvious that there is actually something like "equilibrium" at play in nature. The rest of the book investigates two key campaign events: the party convention and the debates. Holbrook's finding is that if a candidate's popularity is significantly greater than his estimated equilibrium, then that candidate will not receive a significant "bump" in the polls. However, if a candidate's popularity is significantly lower than her estimated equilibrium, then she will likely receive a significant bump in the polls. However, these bumps tend to smooth out as we step backward and look at the bigger picture: as Holbrook concludes, "although campaigns do matter and are relevant determinants of candidate support, national conditions carry more weight in determining the eventual outcome." However, if the estimated equilibrium indicates that each candidate (supposing a two party race) should expect roughly 50 percent of the electorate's support, then campaigns can make a huge difference if done right.









Retrospective or Prospective?, August 12, 2012
Several (most?) good election forecasting models use economic variables to predict election outcomes. The model with which I am most familiar is Ray Fair's regression equation, which includes variables for the number of "good news" quarters (in which the growth rate of the economy eclipses 3.2 percent), the absolute value of inflation or deflation during the incumbent's term, and the growth rate in GDP in the first three quarters of an election year. (See Fair's book, Predicting Presidential Elections and Other Things.) Fair's hypothesis is that economic indicators are predictive of elections, or in the words of James Carville, "it's the economy stupid". In other words many forecasting models hold the premise that voters are retrospective in nature; they base their decisions on past stimuli, for example the number of "good news" quarters. Lockerbie's book seeks to answer the question of whether voters cast their ballots with an eye to the future, which is termed prospective voting, as opposed to only voting retrospectively. Lockerbie operates within the framework that voters try to optimize financial wellbeing (the retrospective counterpart being that voters punish or reward incumbents concerning economic variables [where national GDP growth might be a proxy for a person's financial wellbeing]). In short, Lockerbie is convincing in his analysis that voters do indeed cast their votes with an eye to the future. However, could it be that voters see retrospective evaluations in the same color as prospective evaluations? That is, is there any distinction between the recent past and the near future in terms of financial well being? Lockerbie shows that there is a difference, and that prospective evaluations might even be more powerful indicators than retrospective evaluations. To put his money where his mouth is (and to satisfy those of us who can only detect whether a hypothesis has strength if it can forecast election outcomes reasonably well) Lockerbie uses two variables to predict vote share: the proportion of the electorate who believe they will be worse off financially, and a dummy variable coded for whether or not the incumbent party is seeking a third term in a row. Lockerbie uses data from 1956 to 2004. The results are very good, with most residuals scattering tightly around the 1.5 to 3 percent range, but with a 6.4 difference in predicted share minus actual in 2004. The model also predicts the wrong candidate twice, which is normal for a forecasting model given the historical closeness of several elections in the past.









Excellent Overview, August 1, 2012
A simple theory of voting behavior can be represented by the equation R=(PB)C, with R being the total utility a person receives from voting; B is the utility the person receives if her preferred candidate wins the election; P is the person's belief that her vote will be decisive in the outcome of the election; and C is the cost of the act of voting for the voter. Anthony Downs (author of An Economic Theory of Democracy), the creator of this equation, rightly saw that voting is an irrational action: for many people the product of PB is overwhelmed by the cost, C, of voting such that R is negative. Even so, millions of people vote in American elections. However, since the 1960s only around 55 percent of those eligible to vote in presidential elections do so. This book investigates voter turnout in the United States from an institutional perspective. The institutions that Hill investigates are derivations of the electoral college. For instance, political science literature shows that people are more likely to vote if they believe the race to be close, otherwise their value of PB would be near zero. With the electoral college, though, many states are uncompetetive since the number of people identifying strongly with a certain party overwhelms those who identify with the other party. States like Texas, California and New York are examples of these states. Moreover, a presidential candidate from the Democratic Party would likely run a minimal campaign in Wyoming, if at all. It is estimated that if the way in which electoral votes were partitioned to candidates was not in the form of winnertakeall, voter turnout would increase significantly. Hill suggests states reform their electoral policies such that if a candidate wins 25 percent of a state's popular vote, she will win roughly 25 percent of that state's alloted electoral votes. This is a very reasonable reform that would not require (federal) constitutional amendment. Similarly, Hill argues that American democracy falls short with respect to congressional elections. Something like 80 percent of elections for the House of Representatives are uncompetetive. It is easy to see that in such races many citizens feel that their votes will not matter. The political science literature shows that when a congressional race is for an "open seat" (where the incumbent is not running for reelection) then there is significantly more voter turnout as well as campaign spending (which, as it turns out, increases turnout). On average, the margin of victory is also narrower in such elections. Hill also shows notes that allowing electionday registration increases voter turnout. Some states do not allow citizens to register within 30 days of the election. This seems unreasonable, as a presidential race is most "exciting" nearest to election day. Thus for many, interest in a presidential election only picques in the few weeks preceeding the first Tuesday in November. It would be reasonable to allow these citizens to register on election day. The book is full of evidence supporting reforms, as well as reasons why turnout is much lower in the United States as opposed to other industrialized democracies. One more example that I will mention is the United States' system of separation of powers (this is another institution in Hill's thesis). Evidence shows that the probability of a person's liklihood to vote depends on whether there is a "divided government", meaning whether a single party controls both the presidency and the Congress. A person is less likely to vote if there is a divided government, since the prospective voter thinks that there is less liklihood that his vote will te translated into policy if there is a good chance that his preferred policy will not get past Congress, or conversely, will be vetoed by the president. I generated my own crude regression based on a few economic variables (growth, unemployment) and a few dummy variables (whether there was divided government, the duration of the divided period) and found that there is good evidence that the above notion is true. In sum, this book is an excellent overview on voter turnout in the United States.


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