Sie sind bereits eingeloggt. Klicken Sie auf 2. tolino select Abo, um fortzufahren.
Bitte loggen Sie sich zunächst in Ihr Kundenkonto ein oder registrieren Sie sich bei bücher.de, um das eBook-Abo tolino select nutzen zu können.
Discover the power of mixed models with JMP and JMP Pro.
Mixed models are now the mainstream method of choice for analyzing experimental data. Why? They are arguably the most straightforward and powerful way to handle correlated observations in designed experiments. Reaching well beyond standard linear models, mixed models enable you to make accurate and precise inferences about your experiments and to gain deeper understanding of sources of signal and noise in the system under study. Well-formed fixed and random effects generalize well and help you make the best data-driven…mehr
Discover the power of mixed models with JMP and JMP Pro.
Mixed models are now the mainstream method of choice for analyzing experimental data. Why? They are arguably the most straightforward and powerful way to handle correlated observations in designed experiments. Reaching well beyond standard linear models, mixed models enable you to make accurate and precise inferences about your experiments and to gain deeper understanding of sources of signal and noise in the system under study. Well-formed fixed and random effects generalize well and help you make the best data-driven decisions.
JMP for Mixed Models brings together two of the strongest traditions in SAS software: mixed models and JMP. JMP's groundbreaking philosophy of tight integration of statistics with dynamic graphics is an ideal milieu within which to learn and apply mixed models, also known as hierarchical linear or multilevel models. If you are a scientist or engineer, the methods described herein can revolutionize how you analyze experimental data without the need to write code.
Inside you'll find a rich collection of examples and a step-by-step approach to mixed model mastery. Topics include:
Learning how to appropriately recognize, set up, and interpret fixed and random effects
Extending analysis of variance (ANOVA) and linear regression to numerous mixed model designs
Understanding how degrees of freedom work using Skeleton ANOVA
Analyzing randomized block, split-plot, longitudinal, and repeated measures designs
Introducing more advanced methods such as spatial covariance and generalized linear mixed models
Simulating mixed models to assess power and other important sampling characteristics
Providing a solid framework for understanding statistical modeling in general
Improving perspective on modern dilemmas around Bayesian methods, p-values, and causal inference
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, D ausgeliefert werden.
Die Herstellerinformationen sind derzeit nicht verfügbar.
Autorenporträt
Ruth M. Hummel, PhD, is a Senior Manager of Analytical Education at SAS. Dr. Hummel develops curricula, teaches, and consults to help researchers and practitioners apply statistical methods and analytics to solving problems, predominantly in the health and life sciences. Prior to joining SAS in 2016, she worked at the Environmental Protection Agency as the statistical expert for the Risk Assessment Division of the Office of Pollution Prevention and Toxics, and she taught and consulted at the Pennsylvania State University and at the University of Florida. Dr. Hummel is a co-author of Business Statistics and Analytics in Practice, 9th edition, a business statistics textbook emphasizing simple data mining techniques earlier in the standard curriculum. She has a PhD in statistics from the Pennsylvania State University.
Es gelten unsere Allgemeinen Geschäftsbedingungen: www.buecher.de/agb
Impressum
www.buecher.de ist ein Internetauftritt der buecher.de internetstores GmbH
Geschäftsführung: Monica Sawhney | Roland Kölbl | Günter Hilger
Sitz der Gesellschaft: Batheyer Straße 115 - 117, 58099 Hagen
Postanschrift: Bürgermeister-Wegele-Str. 12, 86167 Augsburg
Amtsgericht Hagen HRB 13257
Steuernummer: 321/5800/1497
USt-IdNr: DE450055826