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Language: English - Education Time: 7 hours and 28 minutes - Level: Elementary, Secondary - Size: 2.72 GB.


Data analysis is one of the leading jobs in the current technology market. As per the forecasts of Glassdoor and World Economic Forum, the demand for data scientists will also increase in the next few years. We are generating huge data every day from different domains like Social Media, Healthcare, Sensor data… we have a great tool to analyze them and the tool is R. R programming is a powerful language used widely for data analysis and statistical computing. It is completely free and has rich repositories for packages.

In this course first, you will learn how to install R and start programming on it. It will also help you to know the programming structures and functions. This R programming in Data Science and Data Analytics covers all the steps of Exploratory data analysis, Data pre-processing, and Modelling process. In EDA sections you will learn how to import data sets and create data frames from it. Then it will help you to visualize the variables using different plots. It will give you an initial structure of your data points. In Data pre-processing sections you will get the full idea of Missing value & outliers treatment and data split methods. Finally, you will be able to generate machine learning models using Linear and Logistic Regression.

This R programming for data science and data analytics is designed for both complete beginners with no programming experience or experienced developers looking to make the jump to Data Science!

Franz Kronthaler ... 367 pages - Language: English - Publisher: ‎Springer; (November, 2022) - ISBN-10: 3662643189 - ISBN-13: 978-3662643181.


This book shows you how to analyze data sets systematically and to use Excel 2019 to extract information from data almost effortlessly. Both are (not) an art! The statistical methods are presented and discussed using a single data set. This makes it clear how the methods build on each other and gradually more and more information can be extracted from the data. The Excel functions used are explained in detail - the procedure can be easily transferred to other data sets. 

Various didactic elements facilitate orientation and working with the book: At the checkpoints, the most important aspects from each chapter are briefly summarized. In the freak knowledge section, more advanced aspects are addressed to whet the appetite for more. All examples are calculated with hand and Excel. Numerous applications and solutions as well as further data sets are available on the author's internet platform.

Richard W. Hamming ... Publisher: ‎Dover Publications; (November, 2004) - Language:‎ English - 880 pages - ISBN-10:‎ 0486439453 - ISBN-13:‎ 978-0486439457.


Understanding calculus is vital to the creative applications of mathematics in numerous areas. This text focuses on the most widely used applications of mathematical methods, including those related to other important fields such as probability and statistics. The four-part treatment begins with algebra and analytic geometry and proceeds to an exploration of the calculus of algebraic functions and transcendental functions and applications. In addition to three helpful appendixes, the text features answers to some of the exercises. Appropriate for advanced undergraduates and graduate students, it is also a practical reference for professionals. 1985 edition. 310 figures. 18 tables.

Ann Lehman, Norm O'Rourke, Larry Hatcher, Edward J. Stepanski ... 481 pages - Language: ‎ English - Publisher: ‎ SAS Institute; (February, 2005) - ISBN-10: ‎1590475763 - ISBN-13: 978-1590475768.


Doing statistics in JMP has never been easier! Learn how to manage JMP data and perform the statistical analyses most commonly used in research in the social sciences and other fields with JMP for Basic Univariate and Multivariate Statistics: A Step-by-Step Guide, authored by Ann Lehman, Norm O'Rourke, Larry Hatcher, and Edward Stepanski. Clearly written instructions guide you through the basic concepts of research and data analysis, enabling you to easily perform statistical analyses and solve problems in real-world research. Step by step, you'll discover how to obtain descriptive and inferential statistics, summarize results, perform a wide range of JMP analyses, interpret the results, and more. Topics include: screening data for errors and selecting subsets with the JMP Distribution platform, computing the coefficient alpha reliability index (Cronbach's alpha) for a multiple-item scale, performing bivariate analyses for all types of variables, performing a one-way analysis of variance (ANOVA), performing a multiple regression, and using the JMP Fit Model platform to perform a one-way multivariate analysis of variance (MANOVA). This user-friendly book introduces researchers and students of the social sciences to JMP and to elementary statistical procedures, while more advanced statistical procedures that are presented make it an invaluable reference guide for experienced researchers as well.

Randall Pruim ... 820 pages - Publisher: American Mathematical Society; 2nd Edition (April, 2018) - Language: English - ISBN-10: ‎1470428482 - ISBN-13: 978-1470428488.

Foundations and Applications of Statistics simultaneously emphasizes both the foundational and the computational aspects of modern statistics. Engaging and accessible, this book is useful to undergraduate students with a wide range of backgrounds and career goals. The exposition immediately begins with statistics, presenting concepts and results from probability along the way. Hypothesis testing is introduced very early, and the motivation for several probability distributions comes from p-value computations. Pruim develops the students' practical statistical reasoning through explicit examples and through numerical and graphical summaries of data that allow intuitive inferences before introducing the formal machinery. The topics have been selected to reflect the current practice in statistics, where computation is an indispensible tool. In this vein, the statistical computing environment $\textsf{R}$ is used throughout the text and is integral to the exposition. Attention is paid to developing students' mathematical and computational skills as well as their statistical reasoning. Linear models, such as regression and ANOVA, are treated with explicit reference to the underlying linear algebra, which is motivated geometrically. Foundations and Applications of Statistics discusses both the mathematical theory underlying statistics and practical applications that make it a powerful tool across disciplines. The book contains ample material for a two-semester course in undergraduate probability and statistics. A one-semester course based on the book will cover hypothesis testing and confidence intervals for the most common situations.

Subal C. Kumbhakar, Hung-Jen Wang, Alan P. Horncastle ... 374 pages - Language: ‎ English - Publisher: ‎ Cambridge Univ. Press; (January, 2015) - ISBN-10: ‎ 1107609461 - ISBN-13: 978-1107609464.


Stochastic Frontier Analysis Using Stata provides practitioners in academia and industry with a step-by-step guide on how to conduct efficiency analysis using the stochastic frontier approach. The authors explain in detail how to estimate production, cost, and profit efficiency and introduce the basic theory of each model in an accessible way, using empirical examples that demonstrate the interpretation and application of models. This book also provides computer code, allowing users to apply the models in their own work, and incorporates the most recent stochastic frontier models developed in academic literature. Such recent developments include models of heteroscedasticity and exogenous determinants of inefficiency, scaling models, panel models with time-varying inefficiency, growth models, and panel models that separate firm effects and persistent and transient inefficiency. Immensely helpful to applied researchers, this book bridges the chasm between theory and practice, expanding the range of applications in which production frontier analysis may be implemented.

MathWorks MATLAB 2022a v9.12.0.1884302  [Size: 20.8 GB] ... MATLAB is a highlevel language and interactive environment that is used by millions of engineers and scientists around the world. It allows you to explore and visualize ideas and collaborate in various disciplines, including signal and image processing, communications, management systems and financial engineering. Whether you’re analyzing data, developing algorithms, or creating models, MATLAB is designed for the way you think and the work you do. MATLAB toolboxes are professionally developed, rigorously tested, and fully documented. MATLAB apps let you see how different algorithms work with your data. Iterate until you’ve got the results you want, then automatically generate a MATLAB program to reproduce or automate your work. Scale your analyses to run on clusters, GPUs, and clouds with only minor code changes. There’s no need to rewrite your code or learn big data programming and out-of-memory techniques. 

Features of Mathworks Matlab: Perform a variety of complex mathematical calculations and heavy + Development environment for managing code, files, and data + Explore ways to achieve this solution + A variety of mathematical functions for linear algebra, statistics, Fourier analysis, optimization, filtering, numerical integration and ... + Drawing two-dimensional and three-dimensional graphics functions for visualizing data as + Design and construction of user interfaces under the programming languages ​​C ++, C or Java + Ability to test and measure the exact functions and graphs + The possibility of communication signal processing, image and video + There are various Jbhabzarhay engineering companies for specific applications such as + Telecommunications, control, fuzzy, estimates, statistics, data collection, simulation systems.

Tonny J. Oyana ... 354 pages - Language: ‎English - Publisher: CRC Press; 2nd edition (September, 2020) - ISBN-10: 0367860856 - ISBN-13:‎ 978-0367860851.


In the five years since the publication of the first edition of Spatial Analysis: Statistics, Visualization, and Computational Methods, many new developments have taken shape regarding the implementation of new tools and methods for spatial analysis with R. The use and growth of artificial intelligence, machine learning and deep learning algorithms with a spatial perspective, and the interdisciplinary use of spatial analysis are all covered in this second edition along with traditional statistical methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis. Spatial Analysis with R: Statistics, Visualization, and Computational Methods, Second Edition provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes.

New in the Second Edition: Includes new practical exercises and worked-out examples using R + Presents a wide range of hands-on spatial analysis worktables and lab exercises + All chapters are revised and include new illustrations of different concepts using data from environmental and social sciences + Expanded material on spatiotemporal methods, visual analytics methods, data science, and computational methods + Explains big data, data management, and data mining

Frederick J. Gravetter, Larry B. Wallnau, Lori-Ann B. Forzano, James E. Witnauer ... 608 pages - Language: English - Publisher:‎ Cengage Learning; 10th edition (January, 2020) - ISBN-10: 0357365291 - ISBN-13: ‎978-0357365298.


Updated with the latest research, Gravetter/Wallnau/Forzano/Witnauer's Essentials of Statistics for the Behavioral Sciences, 10th Edition delivers straightforward instruction, hands-on learning tools and real-world examples to help you go beyond memorizing formulas to truly understanding the hows and whys of statistics. Giving extra focus to the topics students typically struggle with most, the authors take time to fully explain statistical concepts. Integrated applications reinforce concepts, offering further support to ensure that even those with a weak background in mathematics can fully grasp statistics. The authors also illustrate how an understanding of statistical procedures will help you comprehend published findings -- ultimately leading you to become a savvy consumer of information. Also available, the MindTap digital learning solution helps you learn on your own terms.

John Sall, Mia L. Stephens, Ann Lehman, Sheila Loring ... 1017 pages - Language: English - Publisher: SAS Institute; 6th edition (February, 2017).


This book provides hands-on tutorials with just the right amount of conceptual and motivational material to illustrate how to use the intuitive interface for data analysis in JMP. Each chapter features concept-specific tutorials, examples, brief reviews of concepts, step-by-step illustrations, and exercises.Updated for JMP 13, JMP Start Statistics, Sixth Edition includes many new features, including: The redesigned Formula Editor. + New and improved ways to create formulas in JMP directly from the data table or dialogs. + Interface updates, including improved menu layout. + Updates and enhancements in many analysis platforms. + New ways to get data into JMP and to save and share JMP results. + Many new features that make it easier to use JMP.

James Ramsay, Giles Hooker, Spencer Graves ... 202 pages - Publisher: Springer; (April, 2010) - Language: English - ISBN-10: 0387981845 - ISBN-13: 978-0387981840.

The book provides an application-oriented overview of functional analysis, with extended and accessible presentations of key concepts such as spline basis functions, data smoothing, curve registration, functional linear models and dynamic systems. Functional data analysis is put to work in a wide a range of applications, so that new problems are likely to find close analogues in this book. The code in R and Matlab in the book has been designed to permit easy modification to adapt to new data structures and research problems.

From the BackCover: Scientists often collect samples of curves and other functional observations, and develop models where parameters are also functions. This volume in the UseR! Series is aimed at a wide range of readers, and especially those who would like apply these techniques to their research problems.  It complements Functional Data Analysis, Second Edition and Applied Functional Data Analysis: Methods and Case Studies by providing computer code in both the R and Matlab languages for a set of data analyses that showcase functional data analysis techniques. The authors make it easy to get up and running in new applications by adapting the code for the examples, and by being able to access the details of key functions within these pages. This book is accompanied by additional web-based support at http://www.functionaldata.org for applying existing functions and developing new ones in either language. The companion 'fda' package for R includes script files to reproduce nearly all the examples in the book including all but one of the 76 figures.

Glyn Davis, Branko Pecar.... Publication date: ‎(January, 2021) - Language: English.

Statistics for Business Students (ISBN: 978-1-63795-762-2) brings the teaching of statistics into the 21st century. Rather than focusing on mathematics behind formulae, this textbook uses two most used platforms to teach the subject, and these are Microsoft Excel and IBM SPSS. The emphasis is on applications, understanding what the functions deliver, and how to interpret the results.

A brief content of this 756-page book is: Preface + Chapter 1 Data Visualisation + Chapter 2 Descriptive statistics + Chapter 3 Probability distributions + Chapter 4 Sampling distributions + Chapter 5 Point and interval estimates + Chapter 6 Hypothesis testing + Chapter 7 Parametric hypothesis tests + Chapter 8 Nonparametric tests + Chapter 9 Linear correlation and regression analysis + Chapter 10 Introduction to time series data, long term forecasts and seasonality + Chapter 11 Short and medium-term forecasts + Appendices + Index.

Lawrence S. Meyers, Glenn C. Gamst, A. J. Guarino ... 736 pages - Publisher: Wiley; (August, 2013) ... Language: English - ISBN-10: 1118357019 - ISBN-13: 978-1118357019.

Features easy-to-follow insight and clear guidelines to perform data analysis using IBM SPSS: Performing Data Analysis Using IBM SPSS® uniquely addresses the presented statistical procedures with an example problem, detailed analysis, and the related data sets. Data entry procedures, variable naming, and step-by-step instructions for all analyses are provided in addition to IBM SPSS point-and-click methods, including details on how to view and manipulate output. Designed as a user’s guide for students and other interested readers to perform statistical data analysis with IBM SPSS, this book addresses the needs, level of sophistication, and interest in introductory statistical methodology on the part of readers in social and behavioral science, business, health-related, and education programs. Each chapter of Performing Data Analysis Using IBM SPSS covers a particular statistical procedure and offers the following: an example problem or analysis goal, together with a data set; IBM SPSS analysis with step-by-step analysis setup and accompanying screen shots; and IBM SPSS output with screen shots and narrative on how to read or interpret the results of the analysis. The book provides in-depth chapter coverage of: IBM SPSS statistical output - Descriptive statistics procedures - Score distribution assumption evaluations - Bivariate correlation - Regressing (predicting) quantitative and categorical variables -Survival analysis -t Test - ANOVA and ANCOVA - Multivariate group differences - Multidimensional scaling - Cluster analysis - Nonparametric procedures for frequency data. Performing Data Analysis Using IBM SPSS is an excellent text for upper-undergraduate and graduate-level students in courses on social, behavioral, and health sciences as well as secondary education, research design, and statistics. Also an excellent reference, the book is ideal for professionals and researchers in the social, behavioral, and health sciences; applied statisticians; and practitioners working in industry.

Riccardo Russo ... 330 pages - Publisher: Routledge; 2nd edition (November, 2020) - Language: English - ASIN: B08QV74121.


This accessible textbook is for those without a mathematical background (just some notions of basic algebra are sufficient) and provides a comprehensive introduction to all topics covered in introductory behavioural science statistics courses. It includes plenty of real examples to demonstrate approaches in depth based on real psychology experiments utilizing the statistical techniques described. New content in this thoroughly updated second edition includes an introduction to Bayesian statistics which complements the coverage of Classical/Frequentist statistics present in the first edition. It also offers practical details on how to perform analyses using JASP – a globally employed, freely downloadable statistical package. The updated eResources also feature a range of new material including additional exercises so readers can test themselves on what they have learned in the book.

This timely and highly readable text will be invaluable to undergraduate students of psychology and research methods courses in related disciplines, as well as anyone with an interest in understanding and applying the basic concepts and inferential techniques associated with statistics in the behavioural sciences.

Mauro da Cunha Naghettini ... 660 pages - Publisher: Springer; (October, 2016) ... Language: English - ISBN-10: 3319435604 - ISBN-13: 978-3319435602.

This textbook covers the main applications of statistical methods in hydrology. It is written for upper undergraduate and graduate students but can be used as a helpful guide for hydrologists, geographers, meteorologists and engineers. The book is very useful for teaching, as it covers the main topics of the subject and contains many worked out examples and proposed exercises. Starting from simple notions of the essential graphical examination of hydrological data, the book gives a complete account of the role that probability considerations must play during modelling, diagnosis of model fit, prediction and evaluating the uncertainty in model predictions, including the essence of Bayesian application in hydrology and statistical methods under nonstationarity. The book also offers a comprehensive and useful discussion on subjective topics, such as the selection of probability distributions suitable for hydrological variables. On a practical level, it explains MS Excel charting and computing capabilities, demonstrates the use of Winbugs free software to solve Monte Carlo Markov Chain (MCMC) simulations, and gives examples of free R code to solve nonstationary models with nonlinear link functions with climate covariates.

Marco Locatelli, Fabio Schoen ... 445 pages - Publisher: SIAM-Society for Industrial and Applied Mathematics (October, 2013) ... Language: English - ISBN-10: 1611972663 - ISBN-13: 978-1611972665.

This volume contains a thorough overview of the rapidly growing field of global optimization, with chapters on key topics such as complexity, heuristic methods, derivation of lower bounds for minimization problems, and branch-and-bound methods and convergence. The final chapter offers both benchmark test problems and applications of global optimization, such as finding the conformation of a molecule or planning an optimal trajectory for interplanetary space travel. An appendix provides fundamental information on convex and concave functions.

Audience: Global Optimization is intended for Ph.D. students, researchers, and practitioners looking for advanced solution methods to difficult optimization problems. It can be used as a supplementary text in an advanced graduate-level seminar. Contents: Chapter 1: Introduction; Chapter 2: Complexity; Chapter 3: Heuristics; Chapter 4: Lower Bounds; Chapter 5: Branch and Bound; Chapter 6: Problems; Appendix A: Basic Definitions and Results on Convexity; Appendix B: Notation.

Wan-Huan ZHOU, Zhen-Yu YIN, Ka-Veng Yuen ... 475 pages - Publisher: Springer; (November, 2020) ... Language: English - ASIN: B08NG1D7G8.


This book introduces systematically the application of Bayesian probabilistic approach in soil mechanics and geotechnical engineering. Four typical problems are analyzed by using Bayesian probabilistic approach, i.e., to model the effect of initial void ratio on the soil–water characteristic curve (SWCC) of unsaturated soil, to select the optimal model for the prediction of the creep behavior of soft soil under one-dimensional straining, to identify model parameters of soils and to select constitutive model of soils considering critical state concept. This book selects the simple and easy-to-understand Bayesian probabilistic algorithm, so that readers can master the Bayesian method to analyze and solve the problem in a short time. In addition, this book provides MATLAB codes for various algorithms and source codes for constitutive models so that readers can directly analyze and practice.

This book is useful as a postgraduate textbook for civil engineering, hydraulic engineering, transportation, railway, engineering geology and other majors in colleges and universities, and as an elective course for senior undergraduates. It is also useful as a reference for relevant professional scientific researchers and engineers.

Peter J. Brockwell, Richard A. Davis ... 439 pages - Publisher: Springer; 3rd edition (August, 2016) - Language: English.

This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences. It assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This third edition contains detailed instructions for the use of the professional version of the Windows-based computer package ITSM2000, now available as a free download from the Springer Extras website. The logic and tools of time series model-building are developed in detail. Numerous exercises are included and the software can be used to analyze and forecast data sets of the user's own choosing. The book can also be used in conjunction with other time series packages such as those included in R. The programs in ITSM2000 however are menu-driven and can be used with minimal investment of time in the computational details.

The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Many additional special topics are also covered. New to this edition: A chapter devoted to Financial Time Series - Introductions to Brownian motion, Lévy processes and Itô calculus - An expanded section on continuous-time ARMA processes.

Statgraphics Centurion 19.1.1 for x64 [Size: 188 MB] ... Statgraphics Centurion 18 is a comprehensive Windows desktop product for statistical analysis, data visualization and predictive analytics. It contains over 260 procedures covering a wide range of data analysis techniques. Statgraphics 18 features an easy-to-use GUI that does not require learning a complicated command language. Especially helpful to practitioners is the StatAdvisor, which explains the results of statistical analyses in a manner suitable for presentation to non-statisticians. Statgraphics 18 is a major upgrade that contains many new features, including: A new file format for handling big data. The 64-bit version can now analyze datasets containing in excess of 100 million rows. * 9 new interactive Statlets for dynamic data visualization, including sunflower plots, population pyramids, wind roses, and violin plots. * Improved demographic maps, with support for SHP files. * Dialog-box driven procedures for accessing R libraries to use classification and regression trees (CART), text mining, multidimensional scaling, analysis of arbitrarily censored data, and seasonal adjustment with X-13ARIMA-SEATS. * Over a dozen other new statistical procedures, including equivalence analysis and noninferiority testing, orthogonal regression, capability control charts, multivariate tolerance intervals, tests for multivariate normality, and random number generation for multivariate normal distributions. * New definitive screening designs in the DOE Wizard.* A new network installation program which allows users to check out seats for use on individual computers. * Extensive enhancements to the process capability analysis procedures to implement the methods described in the new book by Dr. Neil W. Polhemus, Process Capability Analysis: Estimating Quality to be published by Chapman and Hall/CRC Press in December, 2017.

Dirk P. Kroese; Zdravko I. Botev; Thomas Taimre; Radislav Vaisman .... 532 pages - Language: English - AmazonSIN: B081S6BQ2Y - Publisher: Chapman and Hall/CRC; (November, 2019).


The purpose of Data Science and Machine Learning: Mathematical and Statistical Methods is to provide an accessible, yet comprehensive textbook intended for students interested in gaining a better understanding of the mathematics and statistics that underpin the rich variety of ideas and machine learning algorithms in data science. Key Features: Focuses on mathematical understanding. + Presentation is self-contained, accessible, and comprehensive. + Extensive list of exercises and worked-out examples. + Many concrete algorithms with Python code. + Full color throughout.

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