Some tutors ask students to create some kind of a textbook instead.
If you will forgive me, I will be very simple here. The two points I am making are simple, and do not need to be dressed up in fancy clothing. I want to state the points in a way that they cannot be evaded.
I'm not optimistic that this tactic will work, but I owe it to a field I love to try. If I am right in my criticism of economics—I pray that I am not —then much of what economists do nowadays is a waste of time.
If this is so it is very desirable that we economists do something about it, right now. I was told recently by a former editor of the American Economic Review that he "basically agrees" with what I am saying here. This will not do.
Either you agree with me, and will then of course join me in demanding that economics change right away; or you disagree, in which case it is incumbent upon you as a serious scientist to explain exactly why I am mistaken.
The usual objections to mathematical and statistical reasoning in economics seem to me to be unsound. For example, it is often said that economic data is not "strong enough to bear the weight of elaborate mathematics and statistics. But a moment's reflection suggests that this cannot in general be true.
Data on stock-market transactions, for example, are available in unlimited amounts, whereas data on neutron stars or the early days of universe are strictly limited.
Interestingly, it has also been long argued I find explicit statements in the s, and by Gerard Debreu more recently that the weakness of the data is a reason for mathematics, the notion being that economists must therefore rely on axiom and proof.
For the same reason as its opposite, and for some additional reasons, the argument is unsound. One hears sometimes that economic theory is not sufficiently developed to "bear the weight.
Surely the assumptions of Nash equilibrium can bear all the mathematical weight one wishes to pile onto them. Some say that mathematics is inherently too "abstract. That variables other than the life cycle contribute to savings is true, but that is no argument against Franco Modigliani's life and work.
And some say, as Walras characterized the position inthat "human liberty will never allow itself to be cast into equations. The kind of mathematics used in economics is typically that of the Department of Mathematics, not that of the departments of Physics or of Engineering.
It is existence-theorem, qualitative athematics. It is of no use for science. The kind of statistics used in economics is that of Department of Statistics, which is also a species of "existence theorems.
But this, too, is of no use for science. The first, mathematical error has characterized economics since its beginning. It has nothing, really, to do with mathematics, since it can be committed, and was, in entirely verbal economics, such as that of Ricardo.
But the coming of Mathematics-Department mathematics, which never asks how large something is, has continued this unhappy tradition.
As Roberto Marchionnatti notes, the first generations of mathematical economists "were chiefly interested in the problems connected with the relationship between mathematical expressions and experimental [I think he means "experiential"] reality.
The second, statistical error has come to dominate economics since the cheapening of calculation in the s. It was brought into economics by Tinbergen and Klein in the s, but in statistics generally it dates back to R.
Fisher in the s and to Karl Pearson in the s. It was an entirely novel obsession, and perfectly consistent with the Scientific Revolution going on at the time. You might call it bourgeois. How Much will it cost to drain the Somerset Levels? How Much does England's treasure by foreign trade depend on possessing colonies?
How Much is this and How Much that? Adam Smith a century later kept wondering how much wages in Edinburgh differed from those in London too much and how much the colonies by then acquired in England's incessant eighteenth-century wars against France were worth to the home country not much.
By the late eighteenth century, it is surprising to note, the statistical chart had been invented. What is "surprising" is that it hadn't been invented before—another sign that quantitative thinking was novel, at least in the West the Chinese had been collecting statistics on population and prices for centuries.
European states from Sweden to Naples began in the eighteenth century collecting statistics to worry about: The word "statistics" was a coinage of German and Italian enthusiasts for state action in the early eighteenth century, pointing to a story of the state use of numbering.
Then dawned the age of statistics, and everything from drug incarcerations and smoking deaths to the value of a life and the credit rating of Jane Q. The formal and mathematical theory of statistics was largely invented in the s by eugenicists—those clever racists at the origin of so much in the social sciences—and perfected in the twentieth century by agronomists at places like the Rothamsted agricultural experiment station in England or at Iowa State University.
The newly mathematized statistics became a fetish in fields that wanted to be sciences.1 THE MELTING POT IN GA-MATLALA MASERUMULE WITH SPECIAL REFERENCE TO THE BAPEDI CULTURE, LANGUAGE AND DIALECTS.
by. MABULE LIZZY MOKWANA. submitted in fulfilment of the requirements for the degree of. Art and Science of Teaching. by Robert J. Marzano. Table of Contents.
References. Abelson, R. P. (). Statistics as principled barnweddingvt.com, NJ: Lawrence Erlbaum. Oct 22, · WritePass - Essay Writing - Dissertation Topics [TOC]1.
Introduction to Psychology Dissertations2. Categories and List of Dissertation Titles Developmental and Educational Psychology Mental Health and Abnormal Psychology Social Psychology Counselling and Therapy Consumer and Industrial Psychology3.
How to Structure a Psychology Dissertation, . 1 Quantitative Research Dissertation Chapters 4 and 5 (Suggested Content) Information below is suggested content; seek guidance from committee chair about content of all chapters in.
approved Dissertation Research Plan to guide your content for Chapter One. Before beginning the first section, “Background of the Study,” write an introduction to the chapter that begins directly after the CHAPTE R 1.
"Quantitative Ethnography can be read as an engaging first introduction to research methods for students, an introduction to data science and learning analytics for qualitative researchers, or an introduction to the humanities for statisticians and data scientists.