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Introduction to statistics / J.S. Milton, P.M. McTeer and J.J. Corbet.

By: Milton, J. Susan (Janet Susan)Contributor(s): McTeer, P. M | Corbet, J. J. (James J.)Material type: TextTextPublication details: McGraw-Hill, 1996. ISBN: 0070425280; 0071145230DDC classification: 519.5
Contents:
Introduction: Statistics - The Tool of Decision Makers -- Ch. 1. Descriptive Statistics -- Ch. 2. Probability and Counting -- Ch. 3. Random Variables: Discrete Distributions -- Ch. 4. Continuous Distributions: The Normal Curve -- Ch. 5. Inferences on a Single Mean and a Single Variance -- Ch. 6. Inferences on Proportions -- Ch. 7. Statistical Quality Control -- Ch. 8. Comparison of Two Variances and Two Means -- Ch. 9. Regression and Correlation -- Ch. 10. Categorical Data -- Ch. 11. Analysis of Variance -- Ch. 12. Some Distribution-Free Alternatives.
Summary: This introduction to statistics provides an intuitive treatment of both statistics and probability, with a strong emphasis on applications and problem solving. It offers a hands-on approach to learning statistics through student experiments and real-world problems and exercises.
Holdings
Item type Home library Call number Status Date due Barcode Item holds
Two Week Loan Two Week Loan College Lane Learning Resources Centre
Main Shelves
519.5 MIL (Browse shelf(Opens below)) Available 440501257X
Total holds: 0

Enhanced descriptions from Syndetics:

Introduction: Statistics - The Tool of Decision Makers -- Ch. 1. Descriptive Statistics -- Ch. 2. Probability and Counting -- Ch. 3. Random Variables: Discrete Distributions -- Ch. 4. Continuous Distributions: The Normal Curve -- Ch. 5. Inferences on a Single Mean and a Single Variance -- Ch. 6. Inferences on Proportions -- Ch. 7. Statistical Quality Control -- Ch. 8. Comparison of Two Variances and Two Means -- Ch. 9. Regression and Correlation -- Ch. 10. Categorical Data -- Ch. 11. Analysis of Variance -- Ch. 12. Some Distribution-Free Alternatives.

This introduction to statistics provides an intuitive treatment of both statistics and probability, with a strong emphasis on applications and problem solving. It offers a hands-on approach to learning statistics through student experiments and real-world problems and exercises.

undergraduate.

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