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by Gouri K. Bhattacharyya and Richard A. Johnson

Edition: 77Copyright: 1977

Publisher: John Wiley & Sons, Inc.

Published: 1977

International: No

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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.

**Bhattacharyya, Gouri K. : University of Wisconsin-Madison**

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).

**Johnson, Richard A. : University of Wisconsin-Madison**

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.

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 Linear Regression.

Correlation: A Measure of Linear Relationship.

Analysis of Categorized Data.

Design of Experiments and Analysis of Variance.

Nonparametric Inference.

Sample Surveys.

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Summary

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.

Author Bio

**Bhattacharyya, Gouri K. : University of Wisconsin-Madison**

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).

**Johnson, Richard A. : University of Wisconsin-Madison**

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.

Table of Contents

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 Linear Regression.

Correlation: A Measure of Linear Relationship.

Analysis of Categorized Data.

Design of Experiments and Analysis of Variance.

Nonparametric Inference.

Sample Surveys.

Publisher Info

Publisher: John Wiley & Sons, Inc.

Published: 1977

International: No

Published: 1977

International: No

**Bhattacharyya, Gouri K. : University of Wisconsin-Madison**

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).

**Johnson, Richard A. : University of Wisconsin-Madison**

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.

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 Linear Regression.

Correlation: A Measure of Linear Relationship.

Analysis of Categorized Data.

Design of Experiments and Analysis of Variance.

Nonparametric Inference.

Sample Surveys.