Gerhard Tintner’s textbook, first published in 1953 and represented here by its 1954 second printing, presents mathematical and statistical methods as tools for economic investigation. Its organizing purpose is the training of economists who can move between theoretical relationships and empirical estimation:
This book is addressed specifically to the future econometrician—a student of economics who is willing to use the tools of mathematics and statistics in his economic investigations.
The emphasis falls on methodological preparation: mathematical formulation makes economic relationships tractable, while statistics supplies procedures for estimating them and evaluating uncertain evidence. Yet tractability should not be mistaken for an exact description of economic behaviour. Tintner makes that distinction explicit in his treatment of demand:
Linear-demand functions must be considered as approximations to the true demand functions, which may be much more complicated.
Linearity thus serves as a working simplification, not a claim that economic relationships are intrinsically simple. This distinction gives the textbook’s technical instruction an important interpretive qualification: a convenient functional form must remain answerable to the phenomenon it represents.
The later sequence proceeds through sampling theory, hypothesis tests, distribution fitting, regression and correlation, and index numbers. Guidance for further study, answers to odd-numbered exercises, computational tables, and indexes support its use as a course text and working reference. Within the treatment of inference, Tintner connects a test’s formal threshold to the possibility of an erroneous decision:
The probability of the error of the first kind is given by the level of significance.
Statistical testing therefore concerns controlled uncertainty rather than the conversion of sample results into certainty. Estimation likewise requires attention to the characteristics of economic observations. Tintner motivates one technique through its suitability for such data:
One method of estimation, employing the method of least squares, is particularly appropriate with economic data, where frequently we do not have normal distributions.
The book’s central conceptual movement is from simplified economic relationships to methods for their empirical investigation, with repeated attention to the limits of what those methods establish. Its relevance lies in joining mathematical training to statistical judgment: the prospective econometrician must learn not only to calculate, but also to distinguish approximation from description and evidential support from certainty.
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