Modeling Binary Data

Object-Role Modeling Workbook: Data Modeling Exercises using ORM and NORMA  eBooks & eLearning

Posted by AlenMiler at Dec. 25, 2015
Object-Role Modeling Workbook: Data Modeling Exercises using ORM and NORMA

Object-Role Modeling Workbook: Data Modeling Exercises using ORM and NORMA by Dr. Terry Halpin
English | Nov. 20, 2015 | ISBN: 1634621042 | 200 Pages | AZW3/PDF (conv) | 48.19 MB

Object-Role Modeling (ORM) is a fact-based approach to data modeling that expresses the information requirements of any business domain simply in terms of objects that play roles in relationships.

Modeling Binary Correlated Responses using SAS, SPSS and R  eBooks & eLearning

Posted by arundhati at Dec. 1, 2015
Modeling Binary Correlated Responses using SAS, SPSS and R

Jeffrey Wilson, Kent A. Lorenz, "Modeling Binary Correlated Responses using SAS, SPSS and R"
2015 | ISBN-10: 3319238043 | 400 pages | PDF | 4 MB
Meta-analysis of Binary Data Using Profile Likelihood (Chapman & Hall/CRC Interdisciplinary Statistics) by Dankmar Bohning

Meta-analysis of Binary Data Using Profile Likelihood (Chapman & Hall/CRC Interdisciplinary Statistics) by Dankmar Bohning
English | Mar 27, 2008 | ISBN: 1584886307 | 207 Pages | PDF | 1 MB

Providing reliable information on an intervention effect, meta-analysis is a powerful statistical tool for analyzing and combining results from individual studies.

Empirical Modeling and Data Analysis for Engineers and Applied Scientists  eBooks & eLearning

Posted by AvaxGenius at June 7, 2018
Empirical Modeling and Data Analysis for Engineers and Applied Scientists

Empirical Modeling and Data Analysis for Engineers and Applied Scientists By Scott A. Pardo
English | EPUB | 2016 | 255 Pages | ISBN : 3319327674 | 6.38 MB

This textbook teaches advanced undergraduate and first-year graduate students in Engineering and Applied Sciences to gather and analyze empirical observations (data) in order to aid in making design decisions.

Modeling with Data: Tools and Techniques for Scientific Computing (Repost)  eBooks & eLearning

Posted by step778 at Jan. 22, 2018
Modeling with Data: Tools and Techniques for Scientific Computing (Repost)

Ben Klemens, "Modeling with Data: Tools and Techniques for Scientific Computing"
2008 | pages: 471 | ISBN: 069113314X | PDF | 3,7 mb

Introduction to Prescriptive Modeling for Data Science  eBooks & eLearning

Posted by naag at July 25, 2017
Introduction to Prescriptive Modeling for Data Science

Introduction to Prescriptive Modeling for Data Science
MP4 | Video: AVC 1920x1080 | Audio: AAC 48KHz 2ch | Duration: 33M | 966 MB
Genre: eLearning | Language: English

Modeling Longitudinal Data  eBooks & eLearning

Posted by AvaxGenius at May 8, 2017
Modeling Longitudinal Data

Modeling Longitudinal Data By Robert E. Weiss
English | PDF | 2005 | 445 Pages | ISBN : 0387402713 | 3 MB

Longitudinal data are ubiquitous across Medicine, Public Health, Public Policy, Psychology, Political Science, Biology, Sociology and Education, yet many longitudinal data sets remain improperly analyzed. This book teaches the art and statistical science of modern longitudinal data analysis. The author emphasizes specifying, understanding, and interpreting longitudinal data models.

Binary Data Matrix Cube  Graphics

Posted by mposterz at May 3, 2017
Binary Data Matrix Cube

Binary Data Matrix Cube
MOV | 676 MB
Biomechanics of the Musculoskeletal System: Modeling of Data Uncertainty and Knowledge (repost)

Biomechanics of the Musculoskeletal System: Modeling of Data Uncertainty and Knowledge (FOCUS Series) by Tien Tua Dao and Marie-Christine Ho Ba Tho
English | 2014 | ISBN: 1848216025 | 176 pages | PDF | 3 MB

Empirical Modeling and Data Analysis for Engineers and Applied Scientists  eBooks & eLearning

Posted by naag at April 17, 2017
Empirical Modeling and Data Analysis for Engineers and Applied Scientists

Empirical Modeling and Data Analysis for Engineers and Applied Scientists by Scott Pardo
English | 25 July 2016 | ISBN: 3319327674 | 264 Pages | EPUB | 3.96 MB

This textbook teaches advanced undergraduate and first-year graduate students in Engineering and Applied Sciences to gather and analyze empirical observations (data) in order to aid in making design decisions.