Description

Book Synopsis
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.

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 LinearRegression.

Correlation: A Measure of Linear Relationship.

Analysis of Categorized Data.

Design of Experiments and Analysis of Variance.

Nonparametric Inference.

Sample Surveys.

Statistical Concepts Methods 106 Wiley Series in

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    A Paperback / softback by Gouri K. Bhattacharyya, Richard A. Johnson

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      View other formats and editions of Statistical Concepts Methods 106 Wiley Series in by Gouri K. Bhattacharyya

      Publisher: John Wiley & Sons Inc
      Publication Date: Publication Date: 04/05/1977
      ISBN13: 9780471072041, 978-0471072041
      ISBN10: 0471072044

      Description

      Book Synopsis
      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.

      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 LinearRegression.

      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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