Showing results for "jim grayson"
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2015
EN
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. It gives you the "what, why, and how" of using JMP® Pro for building and applying analytic models. This book is designed for business analysts, managers, and practitioners who may not have a solid statistical background, but need to be able to readily apply analytic methods to solve business problems. I...
2022
EN
Come sail away, come sail away……on a quest to find sea monsters!Ten tales about mysterious watery creatures, gods of the sea, aquatic aliens, and a couple of mermaids you do not want to meet. Under the water, in a boat, or just hanging out on the shore, these monsters are playing with all tentacles.Grab your scuba gear, start the motor, or sling on your jetpack. Whether you’re flying far above the water (and hopefully aren’t low on fuel!), catching a...
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Machine Learning with R
R gives you access to the cutting-edge software you need to prepare data for machine learning. No previous knowledge required – this book will take you methodically through every stage of applying machine learning.
2013
EN
Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain...
2015
EN
The fast and easy way to make sense of statistics for big dataDoes the subject of data analysis make you dizzy? You've come to the right place! Statistics For Big Data For Dummies breaks this often-overwhelming subject down into easily digestible parts, offering new and aspiring data analysts the foundation they need to be successful in the field. Inside, you'll find an easy-to-follow introduction to exploratory data analysis, the lowdown on collecting, cl...
Head First Data Analysis
A learner's guide to big numbers, statistics, and good decisions
2009
EN
Today, interpreting data is a critical decision-making factor for businesses and organizations. If your job requires you to manage and analyze all kinds of data, turn to Head First Data Analysis, where you'll quickly learn how to collect and organize data, sort the distractions from the truth, find meaningful patterns, draw conclusions, predict the future, and present your findings to others.Whether you're a product developer researching the market viability of a new produ...
2012
EN
APPROACHES TO QUANTITATIVE RESEARCH is designed for both undergraduate and postgraduate business students who are planning to undertake a research project or dissertation. Due to a lack of formal research training and experience, students can find completing research projects a daunting task. This, coupled with a fear of statistics, can culminate in quite an overwhelming experience for many students. Therefore, APPROACHES TO QUANTITATIVE RESEARCH takes a practical approach to quantitative ...
2014
EN
Using R for Statistics will get you the answers to most of the problems you are likely to encounter when using a variety of statistics. This book is a problem-solution primer for using R to set up your data, pose your problems and get answers using a wide array of statistical tests. The book walks you through R basics and how to use R to accomplish a wide variety statistical operations.You'll be able to navigate the R system, enter and import data, manipulate datasets, ca...
2011
EN
Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover patterns on which to base marketing objectives.This book looks at both classical and ...
2009
EN
The Handbook of Statistical Analysis and Data Mining Applications is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers (both academic and industrial) through all stages of data analysis, model building and implementation. The Handbook helps one discern the technical and business problem, understand the strengths and weaknesses of modern data mining algorithms, and employ the right statistical methods for practical application. ...
2009
EN
This book presents the basic procedures for utilizing SAS Enterprise Guide to analyze statistical data. SAS Enterprise Guide is a graphical user interface (point and click) to the main SAS application. Each chapter contains a brief conceptual overview and then guides the reader through concrete step-by-step examples to complete the analyses. The eleven sections of the book cover a wide range of statistical procedures including descriptive statistics, correlation and simple regression, t te...
Statistical Methods for Organizational Research
Theory and Practice
2004
EN
This clearly written textbook clarifies the concepts underpinning descriptive and inferential statistics in organizational research. Acting as much more than a theoretical reference tool, step-by-step it guides readers through the various key stages of successful data analysis.Covering everything from introductory descriptive statistics to advanced
Latent Variable Modeling Using R
A Step-by-Step Guide
2014
EN
Accessible
This step-by-step guide is written for R and latent variable model (LVM) novices. Utilizing a path model approach and focusing on the lavaan package, this book is designed to help readers quickly understand LVMs and their analysis in R. The author reviews the reasoning behind the syntax selected and provides examples that demonstrate how to analyze data for a variety of LVMs. Featuring examples applicable to psychology, education, business, and ot...











