Del 106 i serien Wiley Series in Probability and Statistics

Statistical Concepts and Methods

Häftad, Engelska, 1977

AvGouri K. Bhattacharyya,Richard A. Johnson

4 199 kr

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A non-mathematical introductory statistics text that combines clear explanation of concepts, an extensive coverage of useful statistical techniques, and numerous illustrations with live data from diverse fields. Emphasizes assumptions and limitations of the statistical methods so that violations of assumptions can be avoided.

Produktinformation

Utgivningsdatum1977-05-04
Mått160 x 238 x 36 mm
Vikt1 012 g
FormatHäftad
SpråkEngelska
SerieWiley Series in Probability and Statistics
Antal sidor656
FörlagJohn Wiley & Sons Inc
ISBN9780471072041

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Matematisk statistik inom Naturvetenskap och teknik

RICHARD A. JOHNSON, Professor of Statistics at The University of Wisconsin, Madison, received his Ph.D. from the University of Minnesota in 1966. He has been at the University of Wisconsin since 1966, except for a one-semester visiting position at the University of Oslo in 1972. Dr. Johnson is an Associate Editor of the Journal of the American Statistical Association and the Secretary-Treasurer of the Madison Chapter of ASA, and Associate Program Secretary of the Institute of Mathematical Statistics. GOURI K. BHATTACHARYYA is Professor of Statistics at The University of Wisconsin, Madison. He received his B.Sc. (1958) and M.Sc. (1960) in Statistics from Calcutta University and his Ph.D. (1966) from the University of California, Berkeley. He has taught at The University of Wisconsin since 1966 with two one-year visiting positions in India at the Indian Institute of Management (1969-70) and the Indian Statistical Institute (1975-76). Dr. Bhattacharyya is a member of the Institute of Mathematical Statistics and Fellow of the Royal Statistical Society (London).

Introduction. Descriptive Study of Data. Elements of Probability. Random Variables and Probability Distributions. Distributions for Counts. Basic Concepts of Testing Hypotheses. The Normal Distribution and Random Samples. Inferences about a Population. Comparing Two Treatments. Regression Analysis: Simple Linear Relation. Regression Analysis: Model Checking and Multiple LinearRegression. Correlation: A Measure of Linear Relationship. Analysis of Categorized Data. Design of Experiments and Analysis of Variance. Nonparametric Inference. Sample Surveys.