Probability and statistics

The Theory of Probability has found a major role in the understanding and explanation of various phenomena in different natural, physical and social sciences e.

The present treatise is intended as a textbook on Quantitative Methods for various examinations.

This book offers the theory of causal analysis and its applications.

Meta-analysis is the statistical combination of previously conducted studies, often from summary statistics but sometimes with individual participant data.

Efficiency and productivity improvement are imperative for businesses to remain competitive in an increasingly dynamic marketplace.

El propósito de este estudio es la de presentar un formato más amigable en el estudio de la Estadística si se compara con otros textos con la  utilización de un lenguaje formal pero sencillo de entender y evitando un nivel de desarrollo matemático muy elevado.

Choose statistically significant stock selection models using SAS(R)Portfolio and Investment Analysis with SAS : Financial Modeling Techniques for Optimization is an introduction to using SAS to choose statistically significant stock selection models, create mean-variance efficient portfolios, and aggressively invest to maximize the geometric mean.

Choose statistically significant stock selection models using SASPortfolio and Investment Analysis with SAS: Financial Modeling Techniques for Optimization is an introduction to using SAS to choose statistically significant stock selection models, create mean-variance efficient portfolios, and aggressively invest to maximize the geometric mean.

Access and clean up data easily using JMP(R)!

Access and clean up data easily using JMP(R)!

A Statistics Equations & Answers Study Guide helps by allowing you to see various different answers and solutions to common and everyday questions that may arrive in a math focused setting.

Probability concepts study the likelihood that an event will happen within a certain frequency within a designated duration.

Statistics equations are the formulas that are used to describe data, to figure out things like means, averages and medians, and essentially to allow us to understand our world a little bit better.

No detailed description available for "e;Causal Inference in R"e;.

This business analytics (BA) text discusses the models based on fact-based data to measure past business performance to guide an organization in visualizing and predicting future business performance and outcomes.

This Second Edition is an essential guide to understanding, modeling, and predicting complex dynamical systems using new methods with stochastic tools.

Get the tools you need to use SAS(R) in clinical trial design!

Get the tools you need to use SAS(R) in clinical trial design!

SAS(R) OnDemand for Academics is now the primary software choice for learners.

SAS(R) OnDemand for Academics is now the primary software choice for learners.

Building Better Models with JMP(R) Pro provides an example-based introduction to business analytics, with a proven process that guides you in the application of modeling tools and concepts.

Building Better Models with JMP Pro provides an example-based introduction to business analytics, with a proven process that guides you in the application of modeling tools and concepts.

Strategies for Formulations Development: A Step-by-Step Guide Using JMP is based on the authors' significant practical experience partnering with scientists to develop strategies to accelerate the formulation (mixtures) development process.

Strategies for Formulations Development: A Step-by-Step Guide Using JMP is based on the authors' significant practical experience partnering with scientists to develop strategies to accelerate the formulation (mixtures) development process.

Applied Data Mining for Forecasting Using SAS, by Tim Rey, Arthur Kordon, and Chip Wells, introduces and describes approaches for mining large time series data sets.

Bridging the gap between statistics texts and SAS documentation, Elementary Statistics Using SAS is written for those who want to perform analyses to solve problems.

Provides a concise yet complete foundational knowledge of the business of healthcare.

Provides a concise yet complete foundational knowledge of the business of healthcare.

This tutorial for data analysts new to SAS Enterprise Guide and SAS Enterprise Miner provides valuable experience using powerful statistical software to complete the kinds of business analytics common to most industries.

This tutorial for data analysts new to SAS Enterprise Guide and SAS Enterprise Miner provides valuable experience using powerful statistical software to complete the kinds of business analytics common to most industries.

Data simulation is a fundamental technique in statistical programming and research.

Find guidance on using SAS for multiple imputation and solving common missing data issues.

Find guidance on using SAS for multiple imputation and solving common missing data issues.

SAS Programming with Medicare Administrative Data is the most comprehensive resource available for using Medicare data with SAS.

This book provides beginners with a thorough foundation in SAS macro programming.

Big data: It's unstructured, it's coming at you fast, and there's lots of it.

Statisticians and researchers will find Categorical Data Analysis Using SAS, Third Edition, by Maura Stokes, Charles Davis, and Gary Koch, to be a useful discussion of categorical data analysis techniques as well as an invaluable aid in applying these methods with SAS.

Glenn Walker and Jack Shostak's Common Statistical Methods for Clinical Research with SAS Examples, Third Edition, is a thoroughly updated edition of the popular introductory statistics book for clinical researchers.

In SAS Statistics by Example, Ron Cody offers up a cookbook approach for doing statistics with SAS.

Improve efficiency while reducing costs in clinical trials with centralized monitoring techniques using JMP and SAS.

Improve efficiency while reducing costs in clinical trials with centralized monitoring techniques using JMP and SAS.

Easy to read and comprehensive, Survival Analysis Using SAS: A Practical Guide, Second Edition, by Paul D.

Partial Least Squares (PLS) is a flexible statistical modeling technique that applies to data of any shape.

This book gives readers a hands-on understanding of Excel-assisted statistical techniques to take effective business decisions.

Each page in the Common Core Math Workouts for grade 8 contains two "e;workouts"e;-one for skills practice and one for applying those skills to solve a problem.

Each page in the Common Core Math Workouts for grade 7 contains two "e;workouts"e;-one for skills practice and one for applying those skills to solve a problem.

Each page in the Common Core Math Workouts for grade 6 contains two "e;workouts"e;-one for skills practice and one for applying those skills to solve a problem.

Mathematics of Networks: Modulus Theory and Convex Optimization explores the question: "e;What can be learned by adapting the theory of p-modulus (and related continuum analysis concepts) to discrete graphs?

Forces shaping human history are complex, but the course of history is undeniably changed on many occasions by conscious acts.

Statistical quantitative methods are vital for financial valuation models and benchmarking machine learning models in finance.