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Applying Regression And Correlation
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Book Synopsis Applying Regression and Correlation by : Jeremy Miles
Download or read book Applying Regression and Correlation written by Jeremy Miles and published by SAGE. This book was released on 2001-03-08 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Takes a look at applying regression analysis in the behavioural sciences by introducing the reader to regression analysis through a simple model-building approach.
Book Synopsis Correlation and Regression by : Philip Bobko
Download or read book Correlation and Regression written by Philip Bobko and published by SAGE Publications. This book was released on 2001-04-10 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: ". . . the writing makes this book interesting to all levels of students. Bobko tackles tough issues in an easy way but provides references for more complex and complete treatment of the subject. . . . there is a familiarity and love of the material that radiates through the words." --Malcolm James Ree, ORGANIZATIONAL RESEARCH METHODS, April 2002 "This book provides one of the clearest treatments of correlations and regression of any statistics book I have seen. . . . Bobko has achieved his objective of making the topics of correlation and regression accessible to students. . . . For someone looking for a very clearly written treatment of applied correlation and regression, this book would be an excellent choice." --Paul E. Spector, University of South Florida "As a quantitative methods instructor, I have reviewed and used many statistical textbooks. This textbook and approach is one of the very best when it comes to user-friendliness, approachability, clarity, and practical utility." --Steven G. Rogelberg, Bowling Green State University Building on the classical examples in the first edition, this updated edition provides students with an accessible textbook on statistical theories in correlation and regression. Taking an applied approach, the author uses concrete examples to help the student thoroughly understand how statistical techniques work and how to creatively apply them based on specific circumstances they face in the "real world." The author uses a layered approach in each chapter, first offering the student an intuitive understanding of the problems or examples and progressing through to the underlying statistics. This layered approach and the applied examples provide students with the foundation and reasoning behind each technique, so they will be able to use their own judgement to effectively choose from the alternative data analytic options.
Book Synopsis Correlation and Regression Analysis by : Thomas J. Archdeacon
Download or read book Correlation and Regression Analysis written by Thomas J. Archdeacon and published by Univ of Wisconsin Press. This book was released on 1994 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: A blueprint for historians to understand and evaluate the variables and discusses the fundamentals of regression analysis. 2 looks at procedures for assessing the level of association among diagnostic methods for identifying and correcting shortcomings Finally, part 3 presents more advanced topics, including in regression models. quantitative analyses they're likely to encounter in journal literature and monographs on research in the social sciences. ignore the fact that most historians have little background in mathematics would be folly, to decipher equations and follow their logic. Concepts are introduced carefully, and the operation of equations is explained step by step. Annotation copyright by Book News, Inc., Portland, OR
Book Synopsis Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences by : Patricia Cohen
Download or read book Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences written by Patricia Cohen and published by Psychology Press. This book was released on 2014-04-04 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classic text on multiple regression is noted for its nonmathematical, applied, and data-analytic approach. Readers profit from its verbal-conceptual exposition and frequent use of examples. The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple regression and a review of bivariate correlation and regression and other elementary statistical concepts provide a strong foundation for understanding the rest of the text. The third edition features an increased emphasis on graphics and the use of confidence intervals and effect size measures, and an accompanying CD with data for most of the numerical examples along with the computer code for SPSS, SAS, and SYSTAT. Applied Multiple Regression serves as both a textbook for graduate students and as a reference tool for researchers in psychology, education, health sciences, communications, business, sociology, political science, anthropology, and economics. An introductory knowledge of statistics is required. Self-standing chapters minimize the need for researchers to refer to previous chapters.
Book Synopsis Applied Regression Analysis by : Norman R. Draper
Download or read book Applied Regression Analysis written by Norman R. Draper and published by John Wiley & Sons. This book was released on 2014-08-25 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: An outstanding introduction to the fundamentals of regression analysis-updated and expanded The methods of regression analysis are the most widely used statistical tools for discovering the relationships among variables. This classic text, with its emphasis on clear, thorough presentation of concepts and applications, offers a complete, easily accessible introduction to the fundamentals of regression analysis. Assuming only a basic knowledge of elementary statistics, Applied Regression Analysis, Third Edition focuses on the fitting and checking of both linear and nonlinear regression models, using small and large data sets, with pocket calculators or computers. This Third Edition features separate chapters on multicollinearity, generalized linear models, mixture ingredients, geometry of regression, robust regression, and resampling procedures. Extensive support materials include sets of carefully designed exercises with full or partial solutions and a series of true/false questions with answers. All data sets used in both the text and the exercises can be found on the companion disk at the back of the book. For analysts, researchers, and students in university, industrial, and government courses on regression, this text is an excellent introduction to the subject and an efficient means of learning how to use a valuable analytical tool. It will also prove an invaluable reference resource for applied scientists and statisticians.
Book Synopsis Correlation and Regression by : Philip Bobko
Download or read book Correlation and Regression written by Philip Bobko and published by SAGE. This book was released on 2001-04-10 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text takes statistical theory in correlation and regression and makes it accessible to readers using words and equations. Examples are used to explain how the techniques work and under what circumstances some creativity in application is necessary.
Book Synopsis Text Book of Correlations and Regression by : A.K. Sharma
Download or read book Text Book of Correlations and Regression written by A.K. Sharma and published by Discovery Publishing House. This book was released on 2005 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book Correlation and Regression is an outcome of authors long teaching experience of the subject. This book present a thorough treatment of what is required for the students of B.A/B.Sc., of all Indian Universities. It includes fundamental concepts, illustrated examples and application to various problems. These illustrative examples have been selected carefully on such topic and sufficient number of unsolved questions are provided which aims at sharpening the skill of students. Contents: Correlation Analysis, Regression Analysis, Partial and Multiple Correlation.
Book Synopsis Learning Statistics with R by : Daniel Navarro
Download or read book Learning Statistics with R written by Daniel Navarro and published by Lulu.com. This book was released on 2013-01-13 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com
Book Synopsis Linear Regression and Its Application to Economics by : Zdzisław Hellwig
Download or read book Linear Regression and Its Application to Economics written by Zdzisław Hellwig and published by Elsevier. This book was released on 2014-05-12 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear Regression and its Application to Economics presents the economic applications of regression theory. This book discusses the importance of linear regression for multi-dimensional variables. Organized into six chapters, this book begins with an overview of the elementary concepts and the more important definitions and theorems concerning two-dimensional and multi-dimensional random variables. This text then examines the important applications of correlation methods to economics. Other chapters consider the methods of estimating regression parameters. This book discusses as well the methods of testing some statistical hypotheses relevant for practical applications of the correlation analysis. The final chapter deals with the fact that correlation methods can be used not only in static but also in dynamic research. This book is a valuable resource for scientists in economic, agricultural, and technical colleges who deal with economic problems in their research. Graduates of economic and technical colleges employed in different branches of the national economy will also find this book useful.
Book Synopsis Regression Analysis and Linear Models by : Richard B. Darlington
Download or read book Regression Analysis and Linear Models written by Richard B. Darlington and published by Guilford Publications. This book was released on 2016-08-22 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing conceptual understanding over mathematics, this user-friendly text introduces linear regression analysis to students and researchers across the social, behavioral, consumer, and health sciences. Coverage includes model construction and estimation, quantification and measurement of multivariate and partial associations, statistical control, group comparisons, moderation analysis, mediation and path analysis, and regression diagnostics, among other important topics. Engaging worked-through examples demonstrate each technique, accompanied by helpful advice and cautions. The use of SPSS, SAS, and STATA is emphasized, with an appendix on regression analysis using R. The companion website (www.afhayes.com) provides datasets for the book's examples as well as the RLM macro for SPSS and SAS. Pedagogical Features: *Chapters include SPSS, SAS, or STATA code pertinent to the analyses described, with each distinctively formatted for easy identification. *An appendix documents the RLM macro, which facilitates computations for estimating and probing interactions, dominance analysis, heteroscedasticity-consistent standard errors, and linear spline regression, among other analyses. *Students are guided to practice what they learn in each chapter using datasets provided online. *Addresses topics not usually covered, such as ways to measure a variable’s importance, coding systems for representing categorical variables, causation, and myths about testing interaction.
Book Synopsis Machine Learning and Big Data by : Uma N. Dulhare
Download or read book Machine Learning and Big Data written by Uma N. Dulhare and published by John Wiley & Sons. This book was released on 2020-09-01 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for academic and industrial developers, exploring and developing applications in the area of big data and machine learning, including those that are solving technology requirements, evaluation of methodology advances and algorithm demonstrations. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the academic and professional community. The 17 chapters are divided into 5 sections: Theoretical Fundamentals; Big Data and Pattern Recognition; Machine Learning: Algorithms & Applications; Machine Learning's Next Frontier and Hands-On and Case Study. While it dwells on the foundations of machine learning and big data as a part of analytics, it also focuses on contemporary topics for research and development. In this regard, the book covers machine learning algorithms and their modern applications in developing automated systems. Subjects covered in detail include: Mathematical foundations of machine learning with various examples. An empirical study of supervised learning algorithms like Naïve Bayes, KNN and semi-supervised learning algorithms viz. S3VM, Graph-Based, Multiview. Precise study on unsupervised learning algorithms like GMM, K-mean clustering, Dritchlet process mixture model, X-means and Reinforcement learning algorithm with Q learning, R learning, TD learning, SARSA Learning, and so forth. Hands-on machine leaning open source tools viz. Apache Mahout, H2O. Case studies for readers to analyze the prescribed cases and present their solutions or interpretations with intrusion detection in MANETS using machine learning. Showcase on novel user-cases: Implications of Electronic Governance as well as Pragmatic Study of BD/ML technologies for agriculture, healthcare, social media, industry, banking, insurance and so on.
Book Synopsis Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences by : Jacob Cohen
Download or read book Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences written by Jacob Cohen and published by Routledge. This book was released on 2013-06-17 with total page 666 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classic text on multiple regression is noted for its nonmathematical, applied, and data-analytic approach. Readers profit from its verbal-conceptual exposition and frequent use of examples. The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple regression and a review of bivariate correlation and regression and other elementary statistical concepts provide a strong foundation for understanding the rest of the text. The third edition features an increased emphasis on graphics and the use of confidence intervals and effect size measures, and an accompanying website with data for most of the numerical examples along with the computer code for SPSS, SAS, and SYSTAT, at www.psypress.com/9780805822236 . Applied Multiple Regression serves as both a textbook for graduate students and as a reference tool for researchers in psychology, education, health sciences, communications, business, sociology, political science, anthropology, and economics. An introductory knowledge of statistics is required. Self-standing chapters minimize the need for researchers to refer to previous chapters.
Download or read book Biometry written by Robert R. Sokal and published by Macmillan. This book was released on 1995 with total page 918 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offers students with little background in statistical analysis an introduction to a variety of statistical concepts and methods. In addition to the incorporation of computer calculation, this new edition expands on a number of important topics, including the revised Kolmogrov-Smirnov test.
Book Synopsis Applications of Regression Techniques by : Manoranjan Pal
Download or read book Applications of Regression Techniques written by Manoranjan Pal and published by Springer. This book was released on 2019-07-18 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the need to carefully and prudently apply various regression techniques in order to obtain the full benefits. It also describes some of the techniques developed and used by the authors, presenting their innovative ideas regarding the formulation and estimation of regression decomposition models, hidden Markov chain, and the contribution of regressors in the set-theoretic approach, calorie poverty rate, and aggregate growth rate. Each of these techniques has applications that address a number of unanswered questions; for example, regression decomposition techniques reveal intra-household gender inequalities of consumption, intra-household allocation of resources and adult equivalent scales, while Hidden Markov chain models can forecast the results of future elections. Most of these procedures are presented using real-world data, and the techniques can be applied in other similar situations. Showing how difficult questions can be answered by developing simple models with simple interpretation of parameters, the book is a valuable resource for students and researchers in the field of model building.
Book Synopsis Regression Analysis by Example by : Samprit Chatterjee
Download or read book Regression Analysis by Example written by Samprit Chatterjee and published by John Wiley & Sons. This book was released on 2006-10-20 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essentials of regression analysis through practical applications Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgement. Regression Analysis by Example, Fourth Edition has been expanded and thoroughly updated to reflect recent advances in the field. The emphasis continues to be on exploratory data analysis rather than statistical theory. The book offers in-depth treatment of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression. This new edition features the following enhancements: Chapter 12, Logistic Regression, is expanded to reflect the increased use of the logit models in statistical analysis A new chapter entitled Further Topics discusses advanced areas of regression analysis Reorganized, expanded, and upgraded exercises appear at the end of each chapter A fully integrated Web page provides data sets Numerous graphical displays highlight the significance of visual appeal Regression Analysis by Example, Fourth Edition is suitable for anyone with an understanding of elementary statistics. Methods of regression analysis are clearly demonstrated, and examples containing the types of irregularities commonly encountered in the real world are provided. Each example isolates one or two techniques and features detailed discussions of the techniques themselves, the required assumptions, and the evaluated success of each technique. The methods described throughout the book can be carried out with most of the currently available statistical software packages, such as the software package R. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
Book Synopsis Statistical Inference via Data Science: A ModernDive into R and the Tidyverse by : Chester Ismay
Download or read book Statistical Inference via Data Science: A ModernDive into R and the Tidyverse written by Chester Ismay and published by CRC Press. This book was released on 2019-12-23 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference using data science tools widely used in industry, academia, and government. It introduces the tidyverse suite of R packages, including the ggplot2 package for data visualization, and the dplyr package for data wrangling. After equipping readers with just enough of these data science tools to perform effective exploratory data analyses, the book covers traditional introductory statistics topics like confidence intervals, hypothesis testing, and multiple regression modeling, while focusing on visualization throughout. Features: ● Assumes minimal prerequisites, notably, no prior calculus nor coding experience ● Motivates theory using real-world data, including all domestic flights leaving New York City in 2013, the Gapminder project, and the data journalism website, FiveThirtyEight.com ● Centers on simulation-based approaches to statistical inference rather than mathematical formulas ● Uses the infer package for "tidy" and transparent statistical inference to construct confidence intervals and conduct hypothesis tests via the bootstrap and permutation methods ● Provides all code and output embedded directly in the text; also available in the online version at moderndive.com This book is intended for individuals who would like to simultaneously start developing their data science toolbox and start learning about the inferential and modeling tools used in much of modern-day research. The book can be used in methods and data science courses and first courses in statistics, at both the undergraduate and graduate levels.
Book Synopsis Applied Regression Analysis and Experimental Design by : Richard J. Brook
Download or read book Applied Regression Analysis and Experimental Design written by Richard J. Brook and published by Routledge. This book was released on 2018-12-13 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: For a solid foundation of important statistical methods, the concise, single-source text unites linear regression with analysis of experiments and provides students with the practical understanding needed to apply theory in real data analysis problems. Stressing principles while keeping computational and theoretical details at a manageable level, Applied Regression Analysis and Experimental Design features an emphasis on vector geometry and least squares to unify and provide an intuitive basis for most topics covered... abundant examples and exercises using real-life data sets clearly illustrating practical of data analysis...essential exposure to MINITAB and GENSTAT computer packages , including computer printouts...and important background material such as vector and matrix properties and the distributional properties of quadratic forms. Designed to make theory work for students, this clearly written, easy-to-understand work serves as the ideal texts for courses Regression, Experimental Design, and Linear Models in a broad range of disciplines. Moreover, applied statisticians will find the book a useful reference for the general application of the linear model.
