There is good reason to be excited about Linear Algebra. With the world becoming increasingly digital, Linear Algebra is gaining more and more importance. When we send texts, share video, do internet searches, there are Linear Algebra algorithms in the background that make it work. This concise introduction to Linear Algebra is authored by a leading researcher presents a book that covers all the requisite material for a first course on the topic in a more practical way. The book focuses on t...
An Introduction to Probability and Statistics 3e (Wiley Series in Probability and Statistics)
by Vijay K. Rohatgi and A. K. Md. Ehsanes Saleh
A well-balanced introduction to probability theory and mathematical statistics Featuring updated material, An Introduction to Probability and Statistics, Third Edition remains a solid overview to probability theory and mathematical statistics. Divided intothree parts, the Third Edition begins by presenting the fundamentals and foundationsof probability. The second part addresses statistical inference, and the remainingchapters focus on special topics. An Introduction to Probability and Statistic...
Statistics with Matlab. Generalized Linear Models and Nonlinear Regression
by L Marvin
Categorical Data Analysis for the Behavioral and Social Sciences
by Razia Azen and Cindy M Walker
Featuring a practical approach with numerous examples, this book focuses on helping the reader develop a conceptual, rather than technical, understanding of categorical methods, making it a much more accessible text than others on the market. The authors cover common categorical analyses and emphasize specific research questions that can be addressed by each analytic procedure so that readers are able to address the research questions they wish to answer. To achieve this goal, the authors: Revi...
This Second Edition of Myles Hollander and Douglas A. Wolfe's successful Nonparametric Statistical Methods meets the needs of a new generation of users, with completely up-to-date coverage of this important statistical area. Like its predecessor, the revised edition, along with its companion ftp site, aims to equip readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for a given situation. An extensive array of examples drawn from actual exper...
200 Worksheets - Identifying Smallest Number of 5 Digits (200 Days Math Smallest Numbers, #4)
by Kapoo Stem
Statistical Learning for Predictive Analytics
by Edward C Malthouse and Ajit C. Tamhane
30 Multiplication Worksheets with 4-Digit Multiplicands, 2-Digit Multipliers (30 Days Math Multiplication, #8)
by Kapoo Stem
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Effectively Execute Lean Six Sigma Projects using SigmaXL and Minitab Written by a Six Sigma Master Black Belt and a Ph.D., this practical guide to Lean Six Sigma project execution follows the DMAIC (Define, Measure, Analyze, Improve, and Control) roadmap. The many real-world examples used in the boo...
Richard Lomax provides a conceptual, intuitive approach to the subject that requires only a rudimentary knowledge of basic algebra. Concepts are clearly stated and supported by real-life examples. Statistical Concepts features comprehensive coverage in a flexible format so instructors can pick and choose topics. It features topics not traditionally found in other textbooks, such as the layout of the data in ANOVA models, the ANOVA linear models, expected mean squares in ANOVA models, and stepwis...
Fitting Curves and Sourfaces Using MATLAB Functions. Regression, Interpolation, Smoothing and Splines
by Perez C
Introduction to Statistics Using R (Synthesis Lectures on Mathematics and Statistics)
by Mustapha Akinkunmi
Introduction to Statistics Using R is organized into 13 major chapters. Each chapter is broken down into many digestible subsections in order to explore the objectives of the book. There are many real-life practical examples in this book and each of the examples is written in R codes to acquaint the readers with some statistical methods while simultaneously learning R scripts.
Advanced Regression in Excel - The Excel Statistical Master
by Mark Harmon