Introductory StatisticsWiley, 1977 - 650 páginas An updated and revised edition of the popular introduction to statistics for students of economics or business, suitable for a one- or two-semester course. Presents an approach that is generally available only in much more advanced texts, yet uses the simplest mathematics consistent with a sound presentation. This Fifth Edition includes a wealth of new problems and examples (many of them real-life problems drawn from the literature) to support the theoretical discussion. Emphasizes the regression model, including nonlinear and multiple regression. Topics covered include randomization to eliminate bias, exploratory data analysis, graphs, expected value in bidding, the bootstrap, path analysis, robust estimation, maximum likelihood estimation and Bayesian estimation and decisions. |
Contenido
Introduction | 3 |
Descriptive Statistics for Samples | 11 |
1233 | 35 |
Derechos de autor | |
Otras 24 secciones no mostradas
Términos y frases comunes
alternative hypothesis analysis ANOVA Answer true approximately average Bayesian bias binomial cell Chapter chips classical test coefficient confidence interval Construct a 95 correlation defined degrees of freedom difference efficiency equation example fertilizer formula graph H₁ height hypothesis testing income increase independent interval estimate least squares likelihood function linear loss function machines mean and variance median multiple regression normal distribution normal population null hypothesis observations outcome population mean population proportion posterior distribution Pr(E predict prior distribution probability distribution Problem random sample random variable regression line regressors reject relative frequency repeated sample mean sample proportion sample space shown in Figure simple regression slope Solution standard deviation standard error statistician Suppose Table theorem tion true or false two-sided unbiased estimator variation X₁ Y₁ yield zero σ²
Referencias a este libro
Applied Regression Analysis, Linear Models, and Related Methods John Fox Sin vista previa disponible - 1997 |