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- Robert V. Hogg
- Introduction to mathematical statistics
- Print Version
- By Robert V Hogg Introduction To Mathematical Statistics
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Statistics education Robust and nonparametric statistics. Hogg is known for his widely used textbooks on statistics with his Ph. Hogg has received recognition for his research on robust and adaptive nonparametric statistics and for his scholarship on total quality management and statistics education. In , he graduated from the University of Illinois with a bachelor's degree in mathematics. With the goal of becoming an actuary , Hogg matriculated at the mathematics department of the University of Iowa then the " State University of Iowa ".
Robert V. Hogg
Statistics education Robust and nonparametric statistics. Hogg is known for his widely used textbooks on statistics with his Ph. Hogg has received recognition for his research on robust and adaptive nonparametric statistics and for his scholarship on total quality management and statistics education.
In , he graduated from the University of Illinois with a bachelor's degree in mathematics. With the goal of becoming an actuary , Hogg matriculated at the mathematics department of the University of Iowa then the " State University of Iowa ". Hogg earned his Ph. After graduating, Hogg remained at the Mathematics Department, where he remained to become a long-serving professor. Hogg independently discovered a special case of " Basu's theorem ", a few years before the publication by Deb Basu.
The textbook "Hogg and Craig" was innovative, particularly in emphasizing sufficient statistics : Sufficient statistics were treated not only for parametric families but also for nonparametric probability distributions: In particular, the sufficiency and completeness of the order statistics from a continuous distribution were treated. Another innovation was the systematic derivation of the distributions of functions of several random variables by using the change-of-variable method.
As noted before, Craig was Hogg's mentor, helping him to obtain a teaching position while a graduate student and also supervising his thesis. Later, after Hogg had graduated, Craig became a close friend, and served as the best man at Hogg's wedding and later as the " godparent " to each of Hogg's four children.
Indeed, Hogg's son Allen was named after Craig. In Hogg became the founding chair of the new Department of Statistics and Actuarial Science, and he remained as the chair for nineteen years. After serving 51 years as an instructor at the University of Iowa, Hogg became Professor Emeritus in Hogg has been a leader in statistics education in the US.
Hogg's 70th birthday was marked by a conference organized by the Institute of Mathematical Statistics , whose proceedings were published as a special issue of Communications in Statistics — Theory and Methods in ; in the conference proceedings, a list of Hogg's publications appears on pages — Hogg has been recognized internationally as a leading researcher in statistics and as an exemplary professor of statistics who has served as a public spokesperson for the profession.
One of the ASA President's tasks is to arrange an annual meeting, and Hogg's diligence was rewarded by the ASA staff, who presented him with the name tag, " Boss Hogg " after the name of a character in the television series The Dukes of Hazzard. Hogg has also been internationally active on behalf of the statistics profession.
From Wikipedia, the free encyclopedia. Robert V. Hannibal, Missouri. Highlands Ranch, Colorado. Statistical Science. Selected Works of Debabrata Basu. Hughes Aug The American Statistician. Later, in his interview with Randles, Hogg speculates that the anonymous referee was Erich Leo Lehmann. Ghosh , editor. Springer Pages — in Randles. Page mentions four children. Randles declares that Hogg is a leader in statistics education on page of Randles.
Randles reports the MAA prize in on page Calvin, ed. Communications in Statistics — Theory and Methods. Outline Index. Descriptive statistics. Mean arithmetic geometric harmonic Median Mode. Central limit theorem Moments Skewness Kurtosis L-moments. Index of dispersion. Grouped data Frequency distribution Contingency table. Data collection. Sampling stratified cluster Standard error Opinion poll Questionnaire.
Scientific control Randomized experiment Randomized controlled trial Random assignment Blocking Interaction Factorial experiment. Adaptive clinical trial Up-and-Down Designs Stochastic approximation. Cross-sectional study Cohort study Natural experiment Quasi-experiment. Statistical inference. Z -test normal Student's t -test F -test. Bayesian probability prior posterior Credible interval Bayes factor Bayesian estimator Maximum posterior estimator.
Correlation Regression analysis. Pearson product-moment Partial correlation Confounding variable Coefficient of determination. Simple linear regression Ordinary least squares General linear model Bayesian regression. Regression Manova Principal components Canonical correlation Discriminant analysis Cluster analysis Classification Structural equation model Factor analysis Multivariate distributions Elliptical distributions Normal.
Spectral density estimation Fourier analysis Wavelet Whittle likelihood. Nelson—Aalen estimator. Log-rank test. Cartography Environmental statistics Geographic information system Geostatistics Kriging. Namespaces Article Talk. Views Read Edit View history. Help Learn to edit Community portal Recent changes Upload file.
Download as PDF Printable version. United States of America. University of Iowa Ph. University of Illinois. Correlation Regression analysis Correlation Pearson product-moment Partial correlation Confounding variable Coefficient of determination.
Introduction to mathematical statistics
Chapter 0 grew and is growing recursively. Download books for free. Statistics is about the mathematical modeling of observable phenomena, using stochastic models, and about analyzing data: estimating parameters of the model and testing hypotheses. These subjects are discussed in Chapters 3, 4, and 5, respectively. Comprehending as with ease as treaty even more than further will offer each success.
This classic book retains its outstanding ongoing features and continues to provide readers with excellent background material necessary for a successful understanding of mathematical statistics.
For senior and first year graduate level two-semester sequence in probability and mathematical statistics. Requires calculus. Exceptionally clear and impeccably accurate, the fifth edition of this trusted text offers a careful presentation of the probability needed for mathematical statistics and the mathematics of statistical inference.
This course introduces basic descriptive and inferential statistics using both traditional normal and t-distribution and simulation approaches including confidence intervals and hypothesis testing on means one-sample, two-sample, paired , proportions one-sample, two-sample , regression and correlation. The book is also an excellent text for upper-undergraduate and graduate-level students majoring in probability and statistics. These three courses are designed to cover material from the traditional high-school curriculum. Initial placement into these courses is determined by a placement exam.
Copies of the classnotes are on the internet in PDF format as given below. The notes and supplements may contain hyperlinks to posted webpages; the links appear in red fonts. The "Proofs of Theorems" files were prepared in Beamer. These notes have not been classroom tested and may have typographical errors. The catalog description for Mathematical Statistics 1 is: "An introduction to the theory of probability and mathematical statistics.
By Robert V Hogg Introduction To Mathematical Statistics
Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. Hogg and J. McKean and A. Hogg , J. McKean , A. Craig Published Computer Science.
Robert V. Craig , University of Iowa. This classic book retains its outstanding ongoing features and continues to provide readers with excellent background material necessary for a successful understanding of mathematical statistics.
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