Methods of Correlation and Regression Analysis, Linear and Curvilinear

By Mordecai Ezekiel; Karl A. Fox | Go to book overview

Subject Index
Introductory Note. Subjects are classified when they relate to regression and correlation issues, or when they have been used as examples in exercises. The many subjects of individual studies mentioned in Chapter 25 are not indexed, however.
Abscissas, defined, 11
Accuracy of estimate, for multiple curvilinear regressions, 249
for multiple linear regressions, 188
Accuracy of observations, effect on results, 311
Adjustments for number of observations and constants, 300, 302
Agricultural economics, studies in, 441
Algebraic fitting, for joint function, 363
for multiple regression curves, 205
for simple regression curves, 83
Analysis of variance, 388
basic principles of, 396
defined, 396
summary of, 411
Appearance and productivity, studies of, 438
Apple prices, illustrating joint function, 375
Arithmetic average, defined, 2
Assumptions for graphic multiple regression curves, 215
Astronomy, studies of, 440
Auto sales, of European cars, 468
Auto-stopping, used as example, 39
Autocorrelation, adjustments for, 334
significance of, 337
Average, arithmetic, see Arithmetic average
"A" variance, defined, 397
Beef consumption, as example, 199
Beta coefficient, defined, 148
for multiple regressions, 192, 196
sampling significance of, 535
Bias in sampling, 26
Biometrika, 434
Card tabulators, in simple regression, 185
Causation, in social sciences, 2
Check sum, defined, 199
use in computations, 489, 509
Chemical characteristics, studies of, 438
Children's clothing size, studies, 454
Coefficient of correlation, see Correlation
coefficient
Coefficient of determination, 130

-543-

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