Source document. This page reproduces the syllabus this course was written to, as published — its semesters, credits and paper numbers are that document’s, not this site’s. The course itself is studied on its own, in any order.
| Administrative Field | Syllabus Specification |
|---|---|
| Course Title | Applied Statistics II |
| Assigned Credits | 4 Credits Total (Theory: 3 Credits, Practical: 1 Credit) |
| Weekly Academic Contact | 5 Contact Hours Total (Theory: 3 Hours, Lab: 2 Hours) |
Theoretical properties and S-shaped behaviors of Modified Exponential, Logistic, and Gompertz curves. Fitting growth curves using the method of three selected points and the method of partial sums. Concept of operational detrending and analyzing the effect of eliminating the trend component on other underlying components of a time series.
Mechanics of base shifting and recalculating index series under changed baseline parameters. Operational differences between Fixed-base and Chain-base index numbers. Techniques for splicing non-overlapping or revised index number series. Deflating an index number series to evaluate real values over nominal structures. Design, item weighting, and construction of the Index of Industrial Production (IIP), covering provisional Interim and final Revised series.
Introduction to market demand function modeling. Derivation of the price elasticity of demand and partial multi-variable elasticities (income and cross-price elasticities). Types of data required for estimating elasticities (time-series, cross-sectional family-budget, and panel data arrays). Formulation of Leontief's method and Pigou's method from time-series records. Formulation of Pigou's method utilizing family-budget datasets. Empirical applications of Engel's curve and Engel's law. Pareto's power law of income distribution, formulation of the distribution parameters, and visualization via concentration curves (Lorenz curves and Gini ratios).
Introduction to psychometric measurement. Scaling individual test items in terms of latent difficulty levels via normal curve transformations (sigma scaling). Scaling of raw scores on a cognitive test. Linear transformations including \(Z\)-scores and \(Z\) scaling, standard scores, and normalized scores. Properties of \(T\)-scores and percentile scores. Converting subjective ordinal arrays: scaling of rankings and ratings in terms of the normal probability curve area distributions.
Classical True-Score theory foundations. Quantification of error variance and evaluating the standard error of measurement (SEM). Mathematical meaning of the index of reliability and parallel test assumptions. Methods of determining empirical test reliability: the test-retest method, the Rulon method of estimating reliability, and methods of rational equivalence via the Kuder-Richardson formula. Evaluation of the validity of test scores, numerical calculation of validity coefficients, and behavior of validity as a function of test length. Direct structural comparison between reliability and validity metrics. Derivation and calculation parameters for the Intelligence Quotient (IQ) under classical and modern deviation scoring frames.