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Alan Anderson Statistics for Big Data For Dummies


The fast and easy way to make sense of statistics for big data Does 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, cleaning, and organizing data, everything you need to know about interpreting data using common software and programming languages, plain-English explanations of how to make sense of data in the real world, and much more. Data has never been easier to come by, and the tools students and professionals need to enter the world of big data are based on applied statistics. While the word «statistics» alone can evoke feelings of anxiety in even the most confident student or professional, it doesn't have to. Written in the familiar and friendly tone that has defined the For Dummies brand for more than twenty years, Statistics For Big Data For Dummies takes the intimidation out of the subject, offering clear explanations and tons of step-by-step instruction to help you make sense of data mining—without losing your cool. Helps you to identify valid, useful, and understandable patterns in data Provides guidance on extracting previously unknown information from large databases Shows you how to discover patterns available in big data Gives you access to the latest tools and techniques for working in big data If you're a student enrolled in a related Applied Statistics course or a professional looking to expand your skillset, Statistics For Big Data For Dummies gives you access to everything you need to succeed.

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Kristin Jarman H. The Art of Data Analysis. How to Answer Almost Any Question Using Basic Statistics


A friendly and accessible approach to applying statistics in the real world With an emphasis on critical thinking, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics presents fun and unique examples, guides readers through the entire data collection and analysis process, and introduces basic statistical concepts along the way. Leaving proofs and complicated mathematics behind, the author portrays the more engaging side of statistics and emphasizes its role as a problem-solving tool. In addition, light-hearted case studies illustrate the application of statistics to real data analyses, highlighting the strengths and weaknesses of commonly used techniques. Written for the growing academic and industrial population that uses statistics in everyday life, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics highlights important issues that often arise when collecting and sifting through data. Featured concepts include: • Descriptive statistics • Analysis of variance • Probability and sample distributions • Confidence intervals • Hypothesis tests • Regression • Statistical correlation • Data collection • Statistical analysis with graphs Fun and inviting from beginning to end, The Art of Data Analysis is an ideal book for students as well as managers and researchers in industry, medicine, or government who face statistical questions and are in need of an intuitive understanding of basic statistical reasoning.

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Geoff Der Essential Statistics Using SAS University Edition


Students and instructors of statistics courses using SAS University Edition will welcome this book. Learning fundamental statistics is essential to solving problems with SAS. Essential Statistics Using SAS University Edition demonstrates how to use SAS University Edition to apply a variety of statistical methodologies, from the simple to the not-so-simple, to a range of data sets. Learn how to apply the appropriate statistical method to answer a particular question about a data set, and correctly interpret the numerical results that you obtain. SAS University Edition users who are new to SAS or who need a refresher course will benefit from the statistics overview and topics, such as multiple linear regression, logistic regression, and Poisson regression.

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Michael Friendly Visual Statistics


A visually intuitive approach to statistical data analysis Visual Statistics brings the most complex and advanced statistical methods within reach of those with little statistical training by using animated graphics of the data. Using ViSta: The Visual Statistics System-developed by Forrest Young and Pedro Valero-Mora and available free of charge on the Internet-students can easily create fully interactive visualizations from relevant mathematical statistics, promoting perceptual and cognitive understanding of the data's story. An emphasis is placed on a paradigm for understanding data that is visual, intuitive, geometric, and active, rather than one that relies on convoluted logic, heavy mathematics, systems of algebraic equations, or passive acceptance of results. A companion Web site complements the book by further demonstrating the concept of creating interactive and dynamic graphics. The book provides users with the opportunity to view the graphics in a dynamic way by illustrating how to analyze statistical data and explore the concepts of visual statistics. Visual Statistics addresses and features the following topics: * Why use dynamic graphics? * A history of statistical graphics * Visual statistics and the graphical user interface * Visual statistics and the scientific method * Character-based statistical interface objects * Graphics-based statistical interfaces * Visualization for exploring univariate data This is an excellent textbook for undergraduate courses in data analysis and regression, for students majoring or minoring in statistics, mathematics, science, engineering, and computer science, as well as for graduate-level courses in mathematics. The book is also ideal as a reference/self-study guide for engineers, scientists, and mathematicians. With contributions by highly regarded professionals in the field, Visual Statistics not only improves a student's understanding of statistics, but also builds confidence to overcome problems that may have previously been intimidating.

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Speedy Publishing Business Statistics (Speedy Study Guides)


Your business statistics pretty much tells you about trends and to use that information make logical solutions to problems. This guide gives a refresher on the types of data and their sources, the importance and limitations of statistics and other basic ideas on the subject. Students and entrepreneurs will find this guide extremely handy in their day-to-day conquests. Invest in a copy today.

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Dempster Martin Psychology Statistics For Dummies


The introduction to statistics that psychology students can't afford to be without Understanding statistics is a requirement for obtaining and making the most of a degree in psychology, a fact of life that often takes first year psychology students by surprise. Filled with jargon-free explanations and real-life examples, Psychology Statistics For Dummies makes the often-confusing world of statistics a lot less baffling, and provides you with the step-by-step instructions necessary for carrying out data analysis. Psychology Statistics For Dummies: Serves as an easily accessible supplement to doorstop-sized psychology textbooks Provides psychology students with psychology-specific statistics instruction Includes clear explanations and instruction on performing statistical analysis Teaches students how to analyze their data with SPSS, the most widely used statistical packages among students

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Hardin James W. Common Errors in Statistics (and How to Avoid Them)


Praise for the Second Edition «All statistics students and teachers will find in this book a friendly and intelligentguide to . . . applied statistics in practice.» —Journal of Applied Statistics «. . . a very engaging and valuable book for all who use statistics in any setting.» —CHOICE «. . . a concise guide to the basics of statistics, replete with examples . . . a valuablereference for more advanced statisticians as well.» —MAA Reviews Now in its Third Edition, the highly readable Common Errors in Statistics (and How to Avoid Them) continues to serve as a thorough and straightforward discussion of basic statistical methods, presentations, approaches, and modeling techniques. Further enriched with new examples and counterexamples from the latest research as well as added coverage of relevant topics, this new edition of the benchmark book addresses popular mistakes often made in data collection and provides an indispensable guide to accurate statistical analysis and reporting. The authors' emphasis on careful practice, combined with a focus on the development of solutions, reveals the true value of statistics when applied correctly in any area of research. The Third Edition has been considerably expanded and revised to include: A new chapter on data quality assessment A new chapter on correlated data An expanded chapter on data analysis covering categorical and ordinal data, continuous measurements, and time-to-event data, including sections on factorial and crossover designs Revamped exercises with a stronger emphasis on solutions An extended chapter on report preparation New sections on factor analysis as well as Poisson and negative binomial regression Providing valuable, up-to-date information in the same user-friendly format as its predecessor, Common Errors in Statistics (and How to Avoid Them), Third Edition is an excellent book for students and professionals in industry, government, medicine, and the social sciences.

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Rogers L., Willoughby D. Numbers Data and statistics for the non-specialist

Ross Maciejewski Data Representations, Transformations, and Statistics for Visual Reasoning

Ed Swires-Hennessy Presenting Data: How to Communicate Your Message Effectively


A clear easy-to-read guide to presenting your message using statistical data Poor presentation of data is everywhere; basic principles are forgotten or ignored. As a result, audiences are presented with confusing tables and charts that do not make immediate sense. This book is intended to be read by all who present data in any form. The author, a chartered statistician who has run many courses on the subject of data presentation, presents numerous examples alongside an explanation of how improvements can be made and basic principles to adopt. He advocates following four key ‘C’ words in all messages: Clear, Concise, Correct and Consistent. Following the principles in the book will lead to clearer, simpler and easier to understand messages which can then be assimilated faster. Anyone from student to researcher, journalist to policy adviser, charity worker to government statistician, will benefit from reading this book. More importantly, it will also benefit the recipients of the presented data. ‘Ed Swires-Hennessy, a recognised expert in the presentation of statistics, explains and clearly describes a set of “principles” of clear and objective statistical communication. This book should be required reading for all those who present statistics.’ Richard Laux, UK Statistics Authority ‘I think this is a fantastic book and hope everyone who presents data or statistics makes time to read it first.’ David Marder, Chief Media Adviser, Office for National Statistics, UK ‘Ed’s book makes his tried-and-tested material widely available to anyone concerned with understanding and presenting data. It is full of interesting insights, is highly practical and packed with sensible suggestions and nice ideas that you immediately want to try out.’ Dr Shirley Coleman, Principal Statistician, Industrial Statistics Research Unit, School of Mathematics and Statistics, Newcastle University, UK

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Statistics - Wikipedia

Data collection Sampling. When full census data cannot be collected, statisticians collect sample data by developing specific experiment designs and survey samples.Statistics itself also provides tools for prediction and forecasting through statistical models.The idea of making inferences based on sampled data began around the mid-1600s in connection with estimating populations and developing ...

A Beginner's Guide to Statistics - ThoughtCo

Statistics is the study of numerical information, called data. Statisticians acquire, organize, and analyze data. Each part of this process is also scrutinized. The techniques of statistics are applied to a multitude of other areas of knowledge.

U.S. Data and Statistics | USAGov

U.S. Census Data and Statistics The United States Census Bureau provides data about the nation’s people and economy. Every 10 years, it conducts the Population and Housing Census, in which every resident in the United States is counted.

Data Types in Statistics | Built In

Having a good understanding of the different data types, also called measurement scales, is a crucial prerequisite for doing Exploratory Data Analysis (EDA), since you can use certain statistical measurements only for specific data types. You also need to know which data type you are dealing with to choose the right visualization method.

The Importance of Statistics - Statistics By Jim

The field of statistics is the science of learning from data. Statistical knowledge helps you use the proper methods to collect the data, employ the correct analyses, and effectively present the results. Statistics is a crucial process behind how we make discoveries in science, make decisions based on data, and make predictions.

Statistics Definition

Statistics is a form of mathematical analysis that uses quantified models, representations and synopses for a given set of experimental data or real-life studies. Statistics studies methodologies...

Statistics - ThoughtCo

Statistics. The numbers back it up: statistics doesn't have to be hard. Learn to explain data and calculate statistics with beginner to advanced tutorials, tools, worksheets, and formulas for students and teachers.

22 Great Articles About Statistics - For Data Scientists ...

5 Free Statistics eBooks You Need to Read This Autumn Your Guide to Master Hypothesis Testing in Statistics Ten simple rules to use statistics effectively 10 Modern Statistical Concepts Discovered by Data Scientists 12 Statistical and ML Methods Data Scientists Should Know Book: Statistics for Non-Statisticians Data Science Has Been Using Rebel ...

How to Understand and Use Basic Statistics (with Pictures)

Statistics is all about data. It helps us to make sense of all the raw data by systematic organisation and interpretation. Knowing how to use statistics gives you the ability to separate the wheat from the chaff. Steps. Part 1 of 3: Know the Importance of Statistics. 1. Note that statistics are used every day. Have you voted for a politician because he claimed his economic policies would lower ...

Statistics for Data Science - FloydHub Blog

So again, I am reiterating the point on Domain + Coding + Statistics = Data Scientist. Now, getting back to our original dataset, please see below. Right: Sample boxplot, Left: boxplot of Wind (y-axis) against Type (x-axis) The above shown is called the box plot. Please note that we can use many types of plots to perform EDA, like scatterplot, histogram, which gives a very good visual ...

Statistics | science | Britannica

Statistics, the science of collecting, analyzing, presenting, and interpreting data. Governmental needs for census data as well as information about a variety of economic activities provided much of the early impetus for the field of statistics.

13 Statistical World Facts That Even Those Who Hate ...

On average, a person makes 7,500 steps a day with an average life expectancy of 80 years. Using this data, scientists calculated that a person can walk 180,000 kilometers during their lifetime. This means that in your life, you can walk around the equator 4.5 times. 8.

What are Data and What are Statistics? - Data & Statistics ...

Statistics result from data that have been interpreted. Statistics can be in the form of numbers or percentages and they are frequently presented in a table or graph. A statistical table might look like this one from the Statistical Abstract of the United States: Evaluating Data and Statistics

Statistical Data Analysis - Statistics Solutions

Statistics is basically a science that involves data collection, data interpretation and finally, data validation. Statistical data analysis is a procedure of performing various statistical operations. It is a kind of quantitative research, which seeks to quantify the data, and typically, applies some form of statistical analysis.

Big data - Statistics & Facts | Statista

Big data - Statistics & Facts Overview; Key figures; Statistics; Published by Shanhong Liu, Sep 2, 2020 "Big data" refers to data sets that are too large or too complex for traditional data ...

Big Data: 20 Mind-Boggling Facts Everyone Must Read

Big data is not a fad. We are just at the beginning of a revolution that will touch every business and every life on this planet. But loads of people are still treating the concept of big data as ...

Stats 101: What You Need To Know About Statistics ...

Statistics is the process of converting data into information that is usable to people. Collections of numbers are difficult for people to make sense of directly. Statistics is a collection of tools that help people understand the meaning of quantitative data.

Fun Facts - Statistic Brain

About 39,000 gallons of water are used to produce the average car. A car operates at maximum economy, gas-wise, at speeds between 25 and 35 miles per hour. The most children born to one woman was 69, she was a peasant who lived a 40 year life, in which she had 16 twins, 7 triplets, and 4 quadruplets.

Statistics News, Articles | The Scientist Magazine®

The Scientist's articles tagged with: statistics. The basic reproductive R0, along with the more malleable effective reproduction number Re, are centerpieces of most epidemiological models that are informing government responses to COVID-19.

Data and Statistics - Data Module #1: What is Research ...

The Difference Between Data and Statistics. While the terms ‘data’ and ‘statistics’ are often used interchangeably, in scholarly research there is an important distinction between them. data are individual pieces of factual information recorded and used for the purpose of analysis. It is the raw information from which statistics are created. Statistics are the results of data analysis ...

Data tables – Data & Statistics - IEA

Data and statistics Data browser Data tables Charts Explore energy data by category, indicator, country or region Reports All reports. Statistics report Monthly oil statistics. September 2020 Statistics report Monthly natural gas statistics. September 2020 Statistics report ...

Statistics Tutorial - Help on Statistics and Research

This section of the statistics tutorial is about understanding how data is acquired and used. The results of a science investigation often contain much more data or information than the researcher needs. This data-material, or information, is called raw data. To be able to analyze the data sensibly, the raw data is processedinto "output data".

Statistics A-B-C - Eurostat

Data > Database > Browse statistics by theme > Statistics A - Z > Experimental statistics > Bulk download > Web Services > Access to microdata > GISCO:Geographical Information and maps > Metadata > SDMX InfoSpace > Data validation ; Publications > All publications > Digital publications > Statistical books > Manuals and guidelines

Students | This is Statistics

Love data? A career in statistics could be for you. A new national survey by SHRM finds data analysis skills are in high demand and the job growth for statisticians is expected to increase by 33.8% in the next ten years. How Statistics Opens Career Opportunities. March 6, 2020. Learn more about the various career opportunities you can pursue with a background in statistics from Amazon research ...

Data, Probability and Statistics - MATH

Data, Surveys, Probability and Statistics at Math is Fun

Statistics News -- ScienceDaily

Statistics. Read about statistics software, news and research from research institutes around the world.

Top Statistics Courses Online - Updated [September 2020 ...

Learn how to use statistics to interpret complex data sets from a top-rated data science instructor. Whether you’re interested in data analysis, business analytics, or data visualization, Udemy has a course to help you master stats.

Describing statistics | fosbosenglisch

Describing statistics. Gliederung einer Graph-Beschreibung und brauchbare Floskeln: Graph-Beschreibung – Aufbau, Floskeln Tipps zu Formulierung und sprachlichen Gestaltung der Beschreibung eines Graphen: Schritt-für-Schritt-Anleitung – Was sollte man tun, was besser nicht? Vier Beispiele für Graphen mit ausformulierten Beschreibungen: Bar chart – auf Deutsch kommentiertes Beispiel und ...

How to classify data in statistics | StudyPug

For statistical data with interval level of measurement, the zero entry represents a position on the particular scale, but not an inherent value. For example, if a substance has a temperature of zero degrees celsius it does not mean that it has no heat, the zero point in the scale was picked because is the freezing point of water. Notice that data with interval level of measurement is similar ...

UNdata

Popular statistical tables, country (area) and regional profiles . Population. Population, surface area and density; PDF | CSV Updated: 23-Jul-2019; International migrants and refugees

Statistics - SQL Server | Microsoft Docs

Statistics become out-of-date after insert, update, delete, or merge operations change the data distribution in the table or indexed view. The Query Optimizer determines when statistics might be out-of-date by counting the number of data modifications since the last statistics update and comparing the number of modifications to a threshold. The ...

The Statistics Myth: Why Statistics Seems so Hard to Learn ...

Having knowledge about statistics is the only thing necessary to practice statistics. This isn’t true. And it’s not helpful. Yes, the knowledge is necessary, but it is not sufficient. Statistics doesn’t make sense to students because it is taught out of context. Most people don’t really learn statistics until they start analyzing data in their own research. Yes, it makes those classes ...

Big Data - Interesting Statistics, Facts & Figures

Big Data Statistics & Facts for 2017. Below are some key statistics, facts and figures which highlight this growth in data and how important it is for business intelligence and decisions. Posted on 22 February 2017. Big Data – Are You In Control? Mark Mulcahy – Waterford Technologies. Big data is a hot issue in today’s business world. The massive increase in the amount of data collected ...

UNdata | about us

UN data was launched as part of a project in 2005, called "Statistics as a Public Good", whose objectives was to provide free access to global statistics, to educate users about the importance of statistics for evidence-based policy and decision-making and to assist National Statistical Offices of Member Countries to strengthen their data dissemination capabilities. The project was implemented ...

What is Statistics? - University of California, Irvine

Statistics is the science concerned with developing and studying methods for collecting, analyzing, interpreting and presenting empirical data. Statistics is a highly interdisciplinary field; research in statistics finds applicability in virtually all scientific fields and research questions in the various scientific fields motivate the development of new statistical methods and theory. In ...

What is Statistics? - Mathematical techniques to analyze data

Statistics is a collection of mathematical techniques that help to analyze and present data. Statistics is also used in associated tasks such as designing experiments and surveys and planning the collection and analysis of data from these. : To understand what statistics is, it is important to look at the broad categories of problems that are tackled with the help of statistics. It also helps ...

Data & Statistics - IRENA

IRENA’s statistics unit helps members to strengthen their data collection and reporting activities through training and methodological guidance. Member countries are encouraged to participate in this process. Explore IRENA data and statistics by browsing a wide range of topics such as Capacity and Generation, Costs, Finance and more on the menu.

What a p-Value Tells You about Statistical Data - dummies

The alternative hypothesis is the one you would believe if the null hypothesis is concluded to be untrue.The evidence in the trial is your data and the statistics that go along with it. All hypothesis tests ultimately use a p-value to weigh the strength of the evidence (what the data are telling you about the population).The p-value is a number between 0 and 1 and interpreted in the following way:

About Data Science Textbook - TIBCO Software

The Data Science Textbook was formerly known as StatSoft's Electronic Statistics Textbook. It has been provided for free as a public service since 1995. This textbook offers training in the understanding and application of data science. It covers a wide variety of appications, including labratory research (biomedical, agricultural), business statistica, credit scoring, forecasting, social ...

World Statistics - International statistics

World Statistics: international statistics, country population, economic and social data provided by International Organisations.

Introduction to Statistics - analyzemath.com

Descriptive statistics deals with the processing of data without attempting to draw any inferences from it. The data are presented in the form of tables and graphs. The characteristics of the data are described in simple terms. Events that are dealt with include everyday happenings such as accidents, prices of goods, business, incomes, epidemics, sports data, population data. Inferential ...

Statistics – The Writing Center • University of North ...

Still, remember that reading statistics is a bit like being in the middle of a war: trust no one; suspect everyone. 2. What is the data’s background? Data and statistics do not just fall from heaven fully formed. They are always the product of research. Therefore, to understand the statistics, you should also know where they come from.

Importance of Statistics for Data Science | Statistics and ...

Data scientists must have a deep understanding of statistical concepts in order to carry out quantitative analysis on the available data. Therefore, they must learn statistics for data science to be successful – this is a given. However, there are a lot of statistics for data science tutorials available online, and the ones by Acadgild are comprehensive enough to provide you with a thorough ...

Data - Wikipedia

Data are characteristics or information, usually numerical, that are collected through observation. In a more technical sense, data are a set of values of qualitative or quantitative variables about one or more persons or objects, while a datum (singular of data) is a single value of a single variable.. Although the terms "data" and "information" are often used interchangeably, these terms ...

Internet | Statista

Statistics and Market Data about the Internet. This page provides statistics, facts and market data related to internet. This includes information on segments and industries such as social media ...

10 Awesome Reasons Why Statistics Are Important | by John ...

Statistics are important because today we live in the information world and much of this information’s are determined mathematically by Statistics Help. It means to be informed correct data and ...

Statistical Data Sets - univie.ac.at

Statistical Data Sets UCI Machine Learning Repository A very extensive archive with over hundred data collections from applications; get the README file () first UCI Knowledge Discovery in Databases Archive for large data sets ''The primary role of this repository is to enable researchers in knowledge discovery and data mining to scale existing and future data analysis algorithms to very large ...

Australian Migration Statistics - Datasets - data.gov.au

Australian Migration Statistics is a statistical package provided as an accompaniment to the annual publication Australia’s Migration Trends published on the Department of Home Affairs website. The statistical package (first produced for the 2016–17 edition of Australia’s Migration Trends) provides detailed statistics on permanent and temporary migration.

Nathan Yau Data Points. Visualization That Means Something


A fresh look at visualization from the author of Visualize This Whether it's statistical charts, geographic maps, or the snappy graphical statistics you see on your favorite news sites, the art of data graphics or visualization is fast becoming a movement of its own. In Data Points: Visualization That Means Something, author Nathan Yau presents an intriguing complement to his bestseller Visualize This, this time focusing on the graphics side of data analysis. Using examples from art, design, business, statistics, cartography, and online media, he explores both standard-and not so standard-concepts and ideas about illustrating data. Shares intriguing ideas from Nathan Yau, author of Visualize This and creator of flowingdata.com, with over 66,000 subscribers Focuses on visualization, data graphics that help viewers see trends and patterns they might not otherwise see in a table Includes examples from the author's own illustrations, as well as from professionals in statistics, art, design, business, computer science, cartography, and more Examines standard rules across all visualization applications, then explores when and where you can break those rules Create visualizations that register at all levels, with Data Points: Visualization That Means Something.

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David Bowers Medical Statistics from Scratch. An Introduction for Health Professionals


Correctly understanding and using medical statistics is a key skill for all medical students and health professionals. In an informal and friendly style, Medical Statistics from Scratch provides a practical foundation for everyone whose first interest is probably not medical statistics. Keeping the level of mathematics to a minimum, it clearly illustrates statistical concepts and practice with numerous real world examples and cases drawn from current medical literature. This fully revised and updated third edition includes new material on: missing data, random allocation and concealment of data intra-class correlation coefficient effect modification and interaction diagnostic testing and the ROC curve standardisation Medical Statistics from Scratch is an ideal learning partner for all medical students and health professionals needing an accessible introduction, or a friendly refresher, to the fundamentals of medical statistics.

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Hannu Oja Robust Correlation. Theory and Applications


This bookpresents material on both the analysis of the classical concepts of correlation and on the development of their robust versions, as well as discussing the related concepts of correlation matrices, partial correlation, canonical correlation, rank correlations, with the corresponding robust and non-robust estimation procedures. Every chapter contains a set of examples with simulated and real-life data. Key features: Makes modern and robust correlation methods readily available and understandable to practitioners, specialists, and consultants working in various fields. Focuses on implementation of methodology and application of robust correlation with R. Introduces the main approaches in robust statistics, such as Huber’s minimax approach and Hampel’s approach based on influence functions. Explores various robust estimates of the correlation coefficient including the minimax variance and bias estimates as well as the most B- and V-robust estimates. Contains applications of robust correlation methods to exploratory data analysis, multivariate statistics, statistics of time series, and to real-life data. Includes an accompanying website featuring computer code and datasets Features exercises and examples throughout the text using both small and large data sets. Theoretical and applied statisticians, specialists in multivariate statistics, robust statistics, robust time series analysis, data analysis and signal processing will benefit from this book. Practitioners who use correlation based methods in their work as well as postgraduate students in statistics will also find this book useful.

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David Rosenthal A. Statistics for Health Care Management and Administration. Working with Excel


The must-have statistics guide for students of health services Statistics for Health Care Management and Administration is a unique and invaluable resource for students of health care administration and public health. The book introduces students to statistics within the context of health care, focusing on the major data and analysis techniques used in the field. All hands-on instruction makes use of Excel, the most common spreadsheet software that is ubiquitous in the workplace. This new third edition has been completely retooled, with new content on proportions, ANOVA, linear regression, chi-squares, and more, Step-by-step instructions in the latest version of Excel and numerous annotated screen shots make examples easy to follow and understand. Familiarity with statistical methods is essential for health services professionals and researchers, who must understand how to acquire, handle, and analyze data. This book not only helps students develop the necessary data analysis skills, but it also boosts familiarity with important software that employers will be looking for. Learn the basics of statistics in the context of Excel Understand how to acquire data and display it for analysis Master various tests including probability, regression, and more Turn test results into usable information with proper analysis Statistics for Health Care Management and Administration gets students off to a great start by introducing statistics in the workplace context from the very beginning.

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David Unger U Can: Statistics For Dummies


Make studying statistics simple with this easy-to-read resource Wouldn't it be wonderful if studying statistics were easier? With U Can: Statistics I For Dummies, it is! This one-stop resource combines lessons, practical examples, study questions, and online practice problems to provide you with the ultimate guide to help you score higher in your statistics course. Foundational statistics skills are a must for students of many disciplines, and leveraging study materials such as this one to supplement your statistics course can be a life-saver. Because U Can: Statistics I For Dummies contains both the lessons you need to learn and the practice problems you need to put the concepts into action, you'll breeze through your scheduled study time. Statistics is all about collecting and interpreting data, and is applicable in a wide range of subject areas—which translates into its popularity among students studying in diverse programs. So, if you feel a bit unsure in class, rest assured that there is an easy way to help you grasp the nuances of statistics! Understand statistical ideas, techniques, formulas, and calculations Interpret and critique graphs and charts, determine probability, and work with confidence intervals Critique and analyze data from polls and experiments Combine learning and applying your new knowledge with practical examples, practice problems, and expanded online resources U Can: Statistics I For Dummies contains everything you need to score higher in your fundamental statistics course!

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Vladimir Cherkassky Learning from Data


An interdisciplinary framework for learning methodologies—covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied—showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science. Complete with over one hundred illustrations, case studies, and examples making this an invaluable text.

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Gregory Lee Business Statistics Made Easy in SAS


Learn or refresh core statistical methods for business with SAS® and approach real business analytics issues and techniques using a practical approach that avoids complex mathematics and instead employs easy-to-follow explanations.
Business Statistics Made Easy in SAS® is designed as a user-friendly, practice-oriented, introductory text to teach businesspeople, students, and others core statistical concepts and applications. It begins with absolute core principles and takes you through an overview of statistics, data and data collection, an introduction to SAS®, and basic statistics (descriptive statistics and basic associational statistics). The book also provides an overview of statistical modeling, effect size, statistical significance and power testing, basics of linear regression, introduction to comparison of means, basics of chi-square tests for categories, extrapolating statistics to business outcomes, and some topical issues in statistics, such as big data, simulation, machine learning, and data warehousing.
The book steers away from complex mathematical-based explanations, and it also avoids basing explanations on the traditional build-up of distributions, probability theory and the like, which tend to lose the practice-oriented reader. Instead, it teaches the core ideas of statistics through methods such as careful, intuitive written explanations, easy-to-follow diagrams, step-by-step technique implementation, and interesting metaphors.
With no previous SAS experience necessary, Business Statistics Made Easy in SAS® is an ideal introduction for beginners. It is suitable for introductory undergraduate classes, postgraduate courses such as MBA refresher classes, and for the business practitioner. It is compatible with SAS® University Edition.

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Eugene Demidenko Advanced Statistics with Applications in R


Advanced Statistics with Applications in R fills the gap between several excellent theoretical statistics textbooks and many applied statistics books where teaching reduces to using existing packages. This book looks at what is under the hood. Many statistics issues including the recent crisis with p -value are caused by misunderstanding of statistical concepts due to poor theoretical background of practitioners and applied statisticians. This book is the product of a forty-year experience in teaching of probability and statistics and their applications for solving real-life problems. There are more than 442 examples in the book: basically every probability or statistics concept is illustrated with an example accompanied with an R code. Many examples, such as Who said π? What team is better? The fall of the Roman empire, James Bond chase problem, Black Friday shopping, Free fall equation: Aristotle or Galilei , and many others are intriguing. These examples cover biostatistics, finance, physics and engineering, text and image analysis, epidemiology, spatial statistics, sociology, etc. Advanced Statistics with Applications in R teaches students to use theory for solving real-life problems through computations: there are about 500 R codes and 100 datasets. These data can be freely downloaded from the author's website dartmouth. edu/~eugened. This book is suitable as a text for senior undergraduate students with major in statistics or data science or graduate students. Many researchers who apply statistics on the regular basis find explanation of many fundamental concepts from the theoretical perspective illustrated by concrete real-world applications.

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