Methods Multivariate Statistics by Srivastava Muni (21 results)

hardcover. Condition: New. 1st Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

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Condition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.

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hardcover. Condition: New. In shrink wrap. Looks like an interesting title!

Condition: Sehr gut. Auflage: 1. 728 Seiten Buch ist leicht verlagert (schief), kleine Lagerspuren am Buch, Inhalt einwandfrei und ungelesen 449934 Sprache: Englisch Gewicht in Gramm: 1485 25,4 x 18,6 x 4,0 cm, Gebundene Ausgabe.

Condition: As New. Unread book in perfect condition.

Hardcover. Condition: new. Hardcover. Get up-to-speed on the latest methods of multivariate statistics Multivariate statistical methods provide a powerful tool for analyzing data when observations are taken over a period of time on the same subject. With the advent of fast and efficient computers and the availability of computer packages such as S-plus and SAS, multivariate methods once too complex to tackle are now within reach of most researchers and data analysts. With an emphasis on computing techniques in combination with a full understanding of the mathematics behind the methods, Methods of Multivariate Statistics offers an up-to-date account of multivariate methods. Focusing on the maximum likelihood method for estimation, testing of hypotheses, and "profile analysis," this book offers comprehensive discussions of commonly encountered multivariate data and also covers some practical and important problems lacking in other texts. These include: * Missing at-random observations * "Growth Curve Models" and multivariate one-sided tests applicable in pharmaceutical and medical trials * Bootstrap methods * Principal component method for predicting a multivariate response vector * Outlier detection and handling inference when covariance is singular With clear chapter introductions and numerous problem sets, Methods of Multivariate Statistics meets every statistician's need for a comprehensive investigation of the latest methods in multivariate statistics. In this volume, Srivastava examines both random variables that can be quantitatively measured as well as the latest multivariate methods. Most of the methods presented assume that the data has a normal distribution and that there are no outliers. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: New. In this volume, Srivastava examines both random variables that can be quantitatively measured as well as the latest multivariate methods. Most of the methods presented assume that the data has a normal distribution and that there are no outliers. Series: Wiley Series in Probability and Statistics. Num Pages: 728 pages, illustrations. BIC Classification: PBT. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 262 x 185 x 47. Weight in Grams: 1566. . 2002. 1st Edition. Hardcover. . . . .

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Condition: New. pp. xix + 697 Illus.

Hardcover. Condition: new. Hardcover. Get up-to-speed on the latest methods of multivariate statistics Multivariate statistical methods provide a powerful tool for analyzing data when observations are taken over a period of time on the same subject. With the advent of fast and efficient computers and the availability of computer packages such as S-plus and SAS, multivariate methods once too complex to tackle are now within reach of most researchers and data analysts. With an emphasis on computing techniques in combination with a full understanding of the mathematics behind the methods, Methods of Multivariate Statistics offers an up-to-date account of multivariate methods. Focusing on the maximum likelihood method for estimation, testing of hypotheses, and "profile analysis," this book offers comprehensive discussions of commonly encountered multivariate data and also covers some practical and important problems lacking in other texts. These include: * Missing at-random observations * "Growth Curve Models" and multivariate one-sided tests applicable in pharmaceutical and medical trials * Bootstrap methods * Principal component method for predicting a multivariate response vector * Outlier detection and handling inference when covariance is singular With clear chapter introductions and numerous problem sets, Methods of Multivariate Statistics meets every statistician's need for a comprehensive investigation of the latest methods in multivariate statistics. In this volume, Srivastava examines both random variables that can be quantitatively measured as well as the latest multivariate methods. Most of the methods presented assume that the data has a normal distribution and that there are no outliers. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condition: New. In this volume, Srivastava examines both random variables that can be quantitatively measured as well as the latest multivariate methods. Most of the methods presented assume that the data has a normal distribution and that there are no outliers. Series: Wiley Series in Probability and Statistics. Num Pages: 728 pages, illustrations. BIC Classification: PBT. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 262 x 185 x 47. Weight in Grams: 1566. . 2002. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.

Hardcover. Condition: Brand New. 1st edition. 697 pages. 10.25x7.25x1.50 inches. In Stock.

Condition: New. pp. xix + 697.

Hardcover. Condition: new. Hardcover. Get up-to-speed on the latest methods of multivariate statistics Multivariate statistical methods provide a powerful tool for analyzing data when observations are taken over a period of time on the same subject. With the advent of fast and efficient computers and the availability of computer packages such as S-plus and SAS, multivariate methods once too complex to tackle are now within reach of most researchers and data analysts. With an emphasis on computing techniques in combination with a full understanding of the mathematics behind the methods, Methods of Multivariate Statistics offers an up-to-date account of multivariate methods. Focusing on the maximum likelihood method for estimation, testing of hypotheses, and "profile analysis," this book offers comprehensive discussions of commonly encountered multivariate data and also covers some practical and important problems lacking in other texts. These include: * Missing at-random observations * "Growth Curve Models" and multivariate one-sided tests applicable in pharmaceutical and medical trials * Bootstrap methods * Principal component method for predicting a multivariate response vector * Outlier detection and handling inference when covariance is singular With clear chapter introductions and numerous problem sets, Methods of Multivariate Statistics meets every statistician's need for a comprehensive investigation of the latest methods in multivariate statistics. In this volume, Srivastava examines both random variables that can be quantitatively measured as well as the latest multivariate methods. Most of the methods presented assume that the data has a normal distribution and that there are no outliers. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Buch. Condition: Neu. Neuware - Get up-to-speed on the latest methods of multivariate statisticsMultivariate statistical methods provide a powerful tool for analyzing data when observations are taken over a period of time on the same subject. With the advent of fast and efficient computers and the availability of computer packages such as S-plus and SAS, multivariate methods once too complex to tackle are now within reach of most researchers and data analysts. With an emphasis on computing techniques in combination with a full understanding of the mathematics behind the methods, Methods of Multivariate Statistics offers an up-to-date account of multivariate methods. Focusing on the maximum likelihood method for estimation, testing of hypotheses, and 'profile analysis,' this book offers comprehensive discussions of commonly encountered multivariate data and also covers some practical and important problems lacking in other texts. These include:\* Missing at-random observations\* 'Growth Curve Models' and multivariate one-sided tests applicable in pharmaceutical and medical trials\* Bootstrap methods\* Principal component method for predicting a multivariate response vector\* Outlier detection and handling inference when covariance is singularWith clear chapter introductions and numerous problem sets, Methods of Multivariate Statistics meets every statistician's need for a comprehensive investigation of the latest methods in multivariate statistics.