A Mathematical Primer for Social Statistics, Ausgabe 159SAGE, 2009 - 170 Seiten John Fox's A Mathematical Primer for Social Statistics covers many often ignored yet important topics in mathematics and mathematical statistics. This text provides readers with the foundation on which an understanding of applied statistics rests. Intended Audience This book is ideal for advanced undergraduates, graduate students, and researchers in the social sciences who need to understand and use relatively advanced statistical methods but whose mathematical preparation for this work is insufficient. Learn more about "The Little Green Book" QASS Series! Click Here. |
Inhalt
Matrices Linear Algebra and Vector Geometry | 1 |
An Introduction to Calculus | 48 |
Probability and Estimation | 84 |
FmFoxMathematical45609 782008 811 PM Page vii | 113 |
Linear LeastSquares Regression | 152 |
| 165 | |
Andere Ausgaben - Alle anzeigen
Häufige Begriffe und Wortgruppen
algebra Analysis angle applied approaches approximation asymptotic basic Bayesian calculus called chapter coefficients coin column conditional Consequently consider consistent constant continuous covariance defined density function depend determinant differentiate distribution eigenvalues elements entries equal Equation error estimator example expectation Figure first function given graph heads illustrated independent inference integral introduced inverse least-squares likelihood limit linear mathematics maximum maximum-likelihood estimator mean method Models multiplication negative nonzero normally distributed observations obtaining operations orthogonal outcomes parameter partial derivatives particular positive posterior prior probability probability density properties random variable rank regression represent respect sample scalar scale score shown shows simple slope Social solution space statistical sufficient Suppose symmetric symmetric matrix theory unknowns values variance vector zero