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Mathematical statistics for applied econometrics / Charles B. Moss.

By: Material type: TextTextPublication details: Boca Raton : CRC Press, c2015.Description: xx, 343 p. : illustrations ; 24 cmISBN:
  • 9781466594098 (hardcover : alk. paper)
Subject(s): DDC classification:
  • 330.015195 23 M913
Contents:
1. Defining mathematical statistics-- 2. Introduction to statistics, probability, and econometrics-- 3. Random variables and probability distributions-- 4. Moments and moment-generating functions-- 5. Binomial and normal random variables-- 6. Large sample theory-- 7. Point estimation-- 8. Interval estimation-- 9. Testing hypotheses-- 10. Elements of matrix analysis-- 11. Regression applications in econmetrics-- 12. Survey of nonlinear econometric applications-- 13. Conclusions-- Appendices-- Glossary-- References-- Index.
Summary: Mathematical Statistics for Applied Econometrics covers the basics of statistical inference in support of a subsequent course on classical econometrics. The book shows students how mathematical statistics concepts form the basis of econometric formulations. It also helps them think about statistics as more than a toolbox of techniques.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 330.015195 M913 (Browse shelf(Opens below)) Available 136300
Total holds: 0

Includes bibliographical references (pages 337-340) and index.

1. Defining mathematical statistics--
2. Introduction to statistics, probability, and econometrics--
3. Random variables and probability distributions--
4. Moments and moment-generating functions--
5. Binomial and normal random variables--
6. Large sample theory--
7. Point estimation--
8. Interval estimation--
9. Testing hypotheses--
10. Elements of matrix analysis--
11. Regression applications in econmetrics--
12. Survey of nonlinear econometric applications--
13. Conclusions--
Appendices--
Glossary--
References--
Index.

Mathematical Statistics for Applied Econometrics covers the basics of statistical inference in support of a subsequent course on classical econometrics. The book shows students how mathematical statistics concepts form the basis of econometric formulations. It also helps them think about statistics as more than a toolbox of techniques.

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