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Distribution Data Guide

Distribution Data Guide PDF Author:
Publisher:
ISBN:
Category : Marketing
Languages : en
Pages : 466

Book Description


Distribution Data Guide

Distribution Data Guide PDF Author:
Publisher:
ISBN:
Category : Marketing
Languages : en
Pages : 466

Book Description


Distribution Data Guide

Distribution Data Guide PDF Author:
Publisher:
ISBN:
Category : Marketing
Languages : en
Pages : 572

Book Description


Making Sense of Data

Making Sense of Data PDF Author: Glenn J. Myatt
Publisher: John Wiley & Sons
ISBN: 0470101016
Category : Mathematics
Languages : en
Pages : 294

Book Description
A practical, step-by-step approach to making sense out of data Making Sense of Data educates readers on the steps and issues that need to be considered in order to successfully complete a data analysis or data mining project. The author provides clear explanations that guide the reader to make timely and accurate decisions from data in almost every field of study. A step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. With a comprehensive collection of methods from both data analysis and data mining disciplines, this book successfully describes the issues that need to be considered, the steps that need to be taken, and appropriately treats technical topics to accomplish effective decision making from data. Readers are given a solid foundation in the procedures associated with complex data analysis or data mining projects and are provided with concrete discussions of the most universal tasks and technical solutions related to the analysis of data, including: * Problem definitions * Data preparation * Data visualization * Data mining * Statistics * Grouping methods * Predictive modeling * Deployment issues and applications Throughout the book, the author examines why these multiple approaches are needed and how these methods will solve different problems. Processes, along with methods, are carefully and meticulously outlined for use in any data analysis or data mining project. From summarizing and interpreting data, to identifying non-trivial facts, patterns, and relationships in the data, to making predictions from the data, Making Sense of Data addresses the many issues that need to be considered as well as the steps that need to be taken to master data analysis and mining.

Statistics 101

Statistics 101 PDF Author: David Borman
Publisher: Simon and Schuster
ISBN: 1507208189
Category : Mathematics
Languages : en
Pages : 240

Book Description
A comprehensive guide to statistics—with information on collecting, measuring, analyzing, and presenting statistical data—continuing the popular 101 series. Data is everywhere. In the age of the internet and social media, we’re responsible for consuming, evaluating, and analyzing data on a daily basis. From understanding the percentage probability that it will rain later today, to evaluating your risk of a health problem, or the fluctuations in the stock market, statistics impact our lives in a variety of ways, and are vital to a variety of careers and fields of practice. Unfortunately, most statistics text books just make us want to take a snooze, but with Statistics 101, you’ll learn the basics of statistics in a way that is both easy-to-understand and apply. From learning the theory of probability and different kinds of distribution concepts, to identifying data patterns and graphing and presenting precise findings, this essential guide can help turn statistical math from scary and complicated, to easy and fun. Whether you are a student looking to supplement your learning, a worker hoping to better understand how statistics works for your job, or a lifelong learner looking to improve your grasp of the world, Statistics 101 has you covered.

Fundamentals of Data Visualization

Fundamentals of Data Visualization PDF Author: Claus O. Wilke
Publisher: O'Reilly Media
ISBN: 1492031054
Category : Computers
Languages : en
Pages : 390

Book Description
Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization software today, scientists, engineers, and business analysts often have to navigate a bewildering array of visualization choices and options. This practical book takes you through many commonly encountered visualization problems, and it provides guidelines on how to turn large datasets into clear and compelling figures. What visualization type is best for the story you want to tell? How do you make informative figures that are visually pleasing? Author Claus O. Wilke teaches you the elements most critical to successful data visualization. Explore the basic concepts of color as a tool to highlight, distinguish, or represent a value Understand the importance of redundant coding to ensure you provide key information in multiple ways Use the book’s visualizations directory, a graphical guide to commonly used types of data visualizations Get extensive examples of good and bad figures Learn how to use figures in a document or report and how employ them effectively to tell a compelling story

Mind On Statistics 3rd Edition

Mind On Statistics 3rd Edition PDF Author: Robert F. Heckard
Publisher:
ISBN: 9780495019299
Category :
Languages : en
Pages : 770

Book Description


The ASQ Pocket Guide to Statistics for Six Sigma Black Belts

The ASQ Pocket Guide to Statistics for Six Sigma Black Belts PDF Author: Matthew A. Barsalou
Publisher: Quality Press
ISBN: 0873891392
Category : Business & Economics
Languages : en
Pages : 97

Book Description
Six Sigma Black Belts are expected to have the skills of a good experimenter, possessing both a deep understanding of statistics and a knowledge of the industry in which they work. This book is written for the Six Sigma Black Belt who needs an understanding of many statistical methods but does not use all of these methods every day. It is intended to be used as a quick reference, providing basic details and formulas. The methods presented here are laid out according to the Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) phases in which they are typically used. Included in appendices are a flowchart that provides the correct statistical test for a given use and type; flowcharts depicting the five steps for hypothesis testing; the statistical formulas in tables to serve as a quick reference; and statistical tables.

Statistical Methods for Machine Learning

Statistical Methods for Machine Learning PDF Author: Jason Brownlee
Publisher: Machine Learning Mastery
ISBN:
Category : Computers
Languages : en
Pages : 291

Book Description
Statistics is a pillar of machine learning. You cannot develop a deep understanding and application of machine learning without it. Cut through the equations, Greek letters, and confusion, and discover the topics in statistics that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover the importance of statistical methods to machine learning, summary stats, hypothesis testing, nonparametric stats, resampling methods, and much more.

Supreme Court of the State of New York Appellate Division Second Department

Supreme Court of the State of New York Appellate Division Second Department PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 1202

Book Description


Applying and Interpreting Statistics

Applying and Interpreting Statistics PDF Author: Glen McPherson
Publisher: Springer Science & Business Media
ISBN: 1475734352
Category : Mathematics
Languages : en
Pages : 664

Book Description
This book describes the basis, application, and interpretation of statistics, and presents a wide range of univariate and multivariate statistical methodology. The Second Edition retains the unique feature of being written from the users' perspective; it connects statistical models and methods to investigative questions and background information, and connects statistical results with interpretations in plain English. In keeping with this approach, methods are grouped by usage rather than by commonality of statistical methodology.