Testing Statistical Assumptions In Research

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Testing Statistical Assumptions in Research

Author : J. P. Verma
Publisher : John Wiley & Sons
ISBN 13 : 1119528410
Total Pages : 224 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Testing Statistical Assumptions in Research by : J. P. Verma

Download or read book Testing Statistical Assumptions in Research written by J. P. Verma and published by John Wiley & Sons. This book was released on 2019-04-02 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensively teaches the basics of testing statistical assumptions in research and the importance in doing so This book facilitates researchers in checking the assumptions of statistical tests used in their research by focusing on the importance of checking assumptions in using statistical methods, showing them how to check assumptions, and explaining what to do if assumptions are not met. Testing Statistical Assumptions in Research discusses the concepts of hypothesis testing and statistical errors in detail, as well as the concepts of power, sample size, and effect size. It introduces SPSS functionality and shows how to segregate data, draw random samples, file split, and create variables automatically. It then goes on to cover different assumptions required in survey studies, and the importance of designing surveys in reporting the efficient findings. The book provides various parametric tests and the related assumptions and shows the procedures for testing these assumptions using SPSS software. To motivate readers to use assumptions, it includes many situations where violation of assumptions affects the findings. Assumptions required for different non-parametric tests such as Chi-square, Mann-Whitney, Kruskal Wallis, and Wilcoxon signed-rank test are also discussed. Finally, it looks at assumptions in non-parametric correlations, such as bi-serial correlation, tetrachoric correlation, and phi coefficient. An excellent reference for graduate students and research scholars of any discipline in testing assumptions of statistical tests before using them in their research study Shows readers the adverse effect of violating the assumptions on findings by means of various illustrations Describes different assumptions associated with different statistical tests commonly used by research scholars Contains examples using SPSS, which helps facilitate readers to understand the procedure involved in testing assumptions Looks at commonly used assumptions in statistical tests, such as z, t and F tests, ANOVA, correlation, and regression analysis Testing Statistical Assumptions in Research is a valuable resource for graduate students of any discipline who write thesis or dissertation for empirical studies in their course works, as well as for data analysts.

Machine Learning Essentials

Author : Alboukadel Kassambara
Publisher : STHDA
ISBN 13 : 1986406857
Total Pages : 209 pages
Book Rating : 4.9/5 (864 download)

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Book Synopsis Machine Learning Essentials by : Alboukadel Kassambara

Download or read book Machine Learning Essentials written by Alboukadel Kassambara and published by STHDA. This book was released on 2018-03-10 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discovering knowledge from big multivariate data, recorded every days, requires specialized machine learning techniques. This book presents an easy to use practical guide in R to compute the most popular machine learning methods for exploring real word data sets, as well as, for building predictive models. The main parts of the book include: A) Unsupervised learning methods, to explore and discover knowledge from a large multivariate data set using clustering and principal component methods. You will learn hierarchical clustering, k-means, principal component analysis and correspondence analysis methods. B) Regression analysis, to predict a quantitative outcome value using linear regression and non-linear regression strategies. C) Classification techniques, to predict a qualitative outcome value using logistic regression, discriminant analysis, naive bayes classifier and support vector machines. D) Advanced machine learning methods, to build robust regression and classification models using k-nearest neighbors methods, decision tree models, ensemble methods (bagging, random forest and boosting). E) Model selection methods, to select automatically the best combination of predictor variables for building an optimal predictive model. These include, best subsets selection methods, stepwise regression and penalized regression (ridge, lasso and elastic net regression models). We also present principal component-based regression methods, which are useful when the data contain multiple correlated predictor variables. F) Model validation and evaluation techniques for measuring the performance of a predictive model. G) Model diagnostics for detecting and fixing a potential problems in a predictive model. The book presents the basic principles of these tasks and provide many examples in R. This book offers solid guidance in data mining for students and researchers. Key features: - Covers machine learning algorithm and implementation - Key mathematical concepts are presented - Short, self-contained chapters with practical examples.

Testing Statistical Assumptions in Research

Author : J. P. Verma
Publisher : John Wiley & Sons
ISBN 13 : 1119528399
Total Pages : 249 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Testing Statistical Assumptions in Research by : J. P. Verma

Download or read book Testing Statistical Assumptions in Research written by J. P. Verma and published by John Wiley & Sons. This book was released on 2019-03-04 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensively teaches the basics of testing statistical assumptions in research and the importance in doing so This book facilitates researchers in checking the assumptions of statistical tests used in their research by focusing on the importance of checking assumptions in using statistical methods, showing them how to check assumptions, and explaining what to do if assumptions are not met. Testing Statistical Assumptions in Research discusses the concepts of hypothesis testing and statistical errors in detail, as well as the concepts of power, sample size, and effect size. It introduces SPSS functionality and shows how to segregate data, draw random samples, file split, and create variables automatically. It then goes on to cover different assumptions required in survey studies, and the importance of designing surveys in reporting the efficient findings. The book provides various parametric tests and the related assumptions and shows the procedures for testing these assumptions using SPSS software. To motivate readers to use assumptions, it includes many situations where violation of assumptions affects the findings. Assumptions required for different non-parametric tests such as Chi-square, Mann-Whitney, Kruskal Wallis, and Wilcoxon signed-rank test are also discussed. Finally, it looks at assumptions in non-parametric correlations, such as bi-serial correlation, tetrachoric correlation, and phi coefficient. An excellent reference for graduate students and research scholars of any discipline in testing assumptions of statistical tests before using them in their research study Shows readers the adverse effect of violating the assumptions on findings by means of various illustrations Describes different assumptions associated with different statistical tests commonly used by research scholars Contains examples using SPSS, which helps facilitate readers to understand the procedure involved in testing assumptions Looks at commonly used assumptions in statistical tests, such as z, t and F tests, ANOVA, correlation, and regression analysis Testing Statistical Assumptions in Research is a valuable resource for graduate students of any discipline who write thesis or dissertation for empirical studies in their course works, as well as for data analysts.

Learning Statistics with R

Author : Daniel Navarro
Publisher : Lulu.com
ISBN 13 : 1326189727
Total Pages : 617 pages
Book Rating : 4.3/5 (261 download)

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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

Introduction to Robust Estimation and Hypothesis Testing

Author : Rand R. Wilcox
Publisher : Academic Press
ISBN 13 : 0123869838
Total Pages : 713 pages
Book Rating : 4.1/5 (238 download)

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Book Synopsis Introduction to Robust Estimation and Hypothesis Testing by : Rand R. Wilcox

Download or read book Introduction to Robust Estimation and Hypothesis Testing written by Rand R. Wilcox and published by Academic Press. This book was released on 2012-01-12 with total page 713 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book focuses on the practical aspects of modern and robust statistical methods. The increased accuracy and power of modern methods, versus conventional approaches to the analysis of variance (ANOVA) and regression, is remarkable. Through a combination of theoretical developments, improved and more flexible statistical methods, and the power of the computer, it is now possible to address problems with standard methods that seemed insurmountable only a few years ago"--

Applied Statistics: From Bivariate Through Multivariate Techniques

Author : Rebecca M. Warner
Publisher : SAGE
ISBN 13 : 141299134X
Total Pages : 1209 pages
Book Rating : 4.4/5 (129 download)

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Book Synopsis Applied Statistics: From Bivariate Through Multivariate Techniques by : Rebecca M. Warner

Download or read book Applied Statistics: From Bivariate Through Multivariate Techniques written by Rebecca M. Warner and published by SAGE. This book was released on 2013 with total page 1209 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rebecca M. Warner's Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked to think about the meaning of equations. Each chapter presents a complete empirical research example to illustrate the application of a specific method. Although SPSS examples are used throughout the book, the conceptual material will be helpful for users of different programs. Each chapter has a glossary and comprehension questions.

100 Statistical Tests

Author : Gopal K Kanji
Publisher : SAGE
ISBN 13 : 9781412923767
Total Pages : 262 pages
Book Rating : 4.9/5 (237 download)

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Book Synopsis 100 Statistical Tests by : Gopal K Kanji

Download or read book 100 Statistical Tests written by Gopal K Kanji and published by SAGE. This book was released on 2006-08-07 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Expanded and updated, the Third Edition of Gopal Kanji's best-selling resource on statistical tests covers all the most commonly used tests with information on how to calculate and interpret results with simple datasets. The Third Edition now includes: - a new introduction to statistical testing with information to guide even the non-statistician through the book quickly and easily - real-world explanations of how and when to use each test with examples drawn from wide range of disciplines - a useful Classification of Tests table - all the relevant statistical tables for checking critical valu.

Statistics Using Technology, Second Edition

Author : Kathryn Kozak
Publisher : Lulu.com
ISBN 13 : 1329757254
Total Pages : 459 pages
Book Rating : 4.3/5 (297 download)

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Book Synopsis Statistics Using Technology, Second Edition by : Kathryn Kozak

Download or read book Statistics Using Technology, Second Edition written by Kathryn Kozak and published by Lulu.com. This book was released on 2015-12-12 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistics With Technology, Second Edition, is an introductory statistics textbook. It uses the TI-83/84 calculator and R, an open source statistical software, for all calculations. Other technology can also be used besides the TI-83/84 calculator and the software R, but these are the ones that are presented in the text. This book presents probability and statistics from a more conceptual approach, and focuses less on computation. Analysis and interpretation of data is more important than how to compute basic statistical values.

Sports Research with Analytical Solution using SPSS

Author : J. P. Verma
Publisher : John Wiley & Sons
ISBN 13 : 1119206715
Total Pages : 403 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Sports Research with Analytical Solution using SPSS by : J. P. Verma

Download or read book Sports Research with Analytical Solution using SPSS written by J. P. Verma and published by John Wiley & Sons. This book was released on 2016-04-11 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: A step-by-step approach to problem-solving techniques using SPSS® in the fields of sports science and physical education Featuring a clear and accessible approach to the methods, processes, and statistical techniques used in sports science and physical education, Sports Research with Analytical Solution using SPSS® emphasizes how to conduct and interpret a range of statistical analysis using SPSS. The book also addresses issues faced by research scholars in these fields by providing analytical solutions to various research problems without reliance on mathematical rigor. Logically arranged to cover both fundamental and advanced concepts, the book presents standard univariate and complex multivariate statistical techniques used in sports research such as multiple regression analysis, discriminant analysis, cluster analysis, and factor analysis. The author focuses on the treatment of various parametric and nonparametric statistical tests, which are shown through the techniques and interpretations of the SPSS outputs that are generated for each analysis. Sports Research with Analytical Solution using SPSS® also features: Numerous examples and case studies to provide readers with practical applications of the analytical concepts and techniques Plentiful screen shots throughout to help demonstrate the implementation of SPSS outputs Illustrative studies with simulated realistic data to clarify the analytical techniques covered End-of-chapter short answer questions, multiple choice questions, assignments, and practice exercises to help build a better understanding of the presented concepts A companion website with associated SPSS data files and PowerPoint® presentations for each chapter Sports Research with Analytical Solution using SPSS® is an excellent textbook for upper-undergraduate, graduate, and PhD-level courses in research methods, kinesiology, sports science, medicine, nutrition, health education, and physical education. The book is also an ideal reference for researchers and professionals in the fields of sports research, sports science, physical education, and social sciences, as well as anyone interested in learning SPSS.

Statistics for Exercise Science and Health with Microsoft Office Excel

Author : J. P. Verma
Publisher : John Wiley & Sons
ISBN 13 : 1118855175
Total Pages : 1227 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Statistics for Exercise Science and Health with Microsoft Office Excel by : J. P. Verma

Download or read book Statistics for Exercise Science and Health with Microsoft Office Excel written by J. P. Verma and published by John Wiley & Sons. This book was released on 2014-06-30 with total page 1227 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the use of statistics to solve a variety of problems in exercise science and health and provides readers with a solid foundation for future research and data analysis. Statistics for Exercise Science and Health with Microsoft Office Excel: Aids readers in analyzing their own data using the presented statistical techniques combined with Excel Features comprehensive coverage of hypothesis testing and regression models to facilitate modeling in sports science Utilizes Excel to enhance reader competency in data analysis and experimental designs Includes coverage of both binomial and poison distributions with applications in exercise science and health Provides solved examples and plentiful practice exercises throughout in addition to case studies to illustrate the discussed analytical techniques Contains all needed definitions and formulas to aid readers in understanding different statistical concepts and developing the needed skills to solve research problems

Encyclopedia of Research Design

Author : Neil J. Salkind
Publisher : SAGE
ISBN 13 : 1412961270
Total Pages : 1779 pages
Book Rating : 4.4/5 (129 download)

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Book Synopsis Encyclopedia of Research Design by : Neil J. Salkind

Download or read book Encyclopedia of Research Design written by Neil J. Salkind and published by SAGE. This book was released on 2010-06-22 with total page 1779 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Comprising more than 500 entries, the Encyclopedia of Research Design explains how to make decisions about research design, undertake research projects in an ethical manner, interpret and draw valid inferences from data, and evaluate experiment design strategies and results. Two additional features carry this encyclopedia far above other works in the field: bibliographic entries devoted to significant articles in the history of research design and reviews of contemporary tools, such as software and statistical procedures, used to analyze results. It covers the spectrum of research design strategies, from material presented in introductory classes to topics necessary in graduate research; it addresses cross- and multidisciplinary research needs, with many examples drawn from the social and behavioral sciences, neurosciences, and biomedical and life sciences; it provides summaries of advantages and disadvantages of often-used strategies; and it uses hundreds of sample tables, figures, and equations based on real-life cases."--Publisher's description.

Research Design & Statistical Analysis

Author : Arnold D. Well
Publisher : Psychology Press
ISBN 13 : 1135641080
Total Pages : 871 pages
Book Rating : 4.1/5 (356 download)

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Book Synopsis Research Design & Statistical Analysis by : Arnold D. Well

Download or read book Research Design & Statistical Analysis written by Arnold D. Well and published by Psychology Press. This book was released on 2003-01-30 with total page 871 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Free CD contains several real and artificial data sets used in the book in SPSS, SYSTAT, and ASCII formats"--Cover

Repeated Measures Design for Empirical Researchers

Author : J. P. Verma
Publisher : John Wiley & Sons
ISBN 13 : 1119052718
Total Pages : 280 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Repeated Measures Design for Empirical Researchers by : J. P. Verma

Download or read book Repeated Measures Design for Empirical Researchers written by J. P. Verma and published by John Wiley & Sons. This book was released on 2015-08-31 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces the applications of repeated measures design processes with the popular IBM® SPSS® software Repeated Measures Design for Empirical Researchers presents comprehensive coverage of the formation of research questions and the analysis of repeated measures using IBM SPSS and also includes the solutions necessary for understanding situations where the designs can be used. In addition to explaining the computation involved in each design, the book presents a unique discussion on how to conceptualize research problems as well as identify appropriate repeated measures designs for research purposes. Featuring practical examples from a multitude of domains including psychology, the social sciences, management, and sports science, the book helps readers better understand the associated theories and methodologies of repeated measures design processes. The book covers various fundamental concepts involved in the design of experiments, basic statistical designs, computational details, differentiating independent and repeated measures designs, and testing assumptions. Along with an introduction to IBM SPSS software, Repeated Measures Design for Empirical Researchers includes: A discussion of the popular repeated measures designs frequently used by researchers, such as one-way repeated measures ANOVA, two-way repeated measures design, two-way mixed design, and mixed design with two-way MANOVA Coverage of sample size determination for the successful implementation of designing and analyzing a repeated measures study A step-by-step guide to analyzing the data obtained with real-world examples throughout to illustrate the underlying advantages and assumptions A companion website with supplementary IBM SPSS data sets and programming solutions as well as additional case studies Repeated Measures Design for Empirical Researchers is a useful textbook for graduate- and PhD-level students majoring in biostatistics, the social sciences, psychology, medicine, management, sports, physical education, and health. The book is also an excellent reference for professionals interested in experimental designs and statistical sciences as well as statistical consultants and practitioners from other fields including biological, medical, agricultural, and horticultural sciences. J. P. Verma, PhD, is Professor of Statistics and Director of the Center for Advanced Studies at Lakshmibai National Institute of Physical Education, India. Professor Verma is an active researcher in sports modeling and data analysis and has conducted many workshops on research methodology, research designs, multivariate analysis, statistical modeling, and data analysis for students of management, physical education, social science, and economics. He is the author of Statistics for Exercise Science and Health with Microsoft® Office Excel®, also published by Wiley.

Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide

Author : Agency for Health Care Research and Quality (U.S.)
Publisher : Government Printing Office
ISBN 13 : 1587634236
Total Pages : 204 pages
Book Rating : 4.5/5 (876 download)

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Book Synopsis Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide by : Agency for Health Care Research and Quality (U.S.)

Download or read book Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide written by Agency for Health Care Research and Quality (U.S.) and published by Government Printing Office. This book was released on 2013-02-21 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: This User’s Guide is a resource for investigators and stakeholders who develop and review observational comparative effectiveness research protocols. It explains how to (1) identify key considerations and best practices for research design; (2) build a protocol based on these standards and best practices; and (3) judge the adequacy and completeness of a protocol. Eleven chapters cover all aspects of research design, including: developing study objectives, defining and refining study questions, addressing the heterogeneity of treatment effect, characterizing exposure, selecting a comparator, defining and measuring outcomes, and identifying optimal data sources. Checklists of guidance and key considerations for protocols are provided at the end of each chapter. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. More more information, please consult the Agency website: www.effectivehealthcare.ahrq.gov)

Statistical Significance Testing for Natural Language Processing

Author : Rotem Dror
Publisher : Springer Nature
ISBN 13 : 3031021746
Total Pages : 98 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Statistical Significance Testing for Natural Language Processing by : Rotem Dror

Download or read book Statistical Significance Testing for Natural Language Processing written by Rotem Dror and published by Springer Nature. This book was released on 2022-06-01 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-driven experimental analysis has become the main evaluation tool of Natural Language Processing (NLP) algorithms. In fact, in the last decade, it has become rare to see an NLP paper, particularly one that proposes a new algorithm, that does not include extensive experimental analysis, and the number of involved tasks, datasets, domains, and languages is constantly growing. This emphasis on empirical results highlights the role of statistical significance testing in NLP research: If we, as a community, rely on empirical evaluation to validate our hypotheses and reveal the correct language processing mechanisms, we better be sure that our results are not coincidental. The goal of this book is to discuss the main aspects of statistical significance testing in NLP. Our guiding assumption throughout the book is that the basic question NLP researchers and engineers deal with is whether or not one algorithm can be considered better than another one. This question drives the field forward as it allows the constant progress of developing better technology for language processing challenges. In practice, researchers and engineers would like to draw the right conclusion from a limited set of experiments, and this conclusion should hold for other experiments with datasets they do not have at their disposal or that they cannot perform due to limited time and resources. The book hence discusses the opportunities and challenges in using statistical significance testing in NLP, from the point of view of experimental comparison between two algorithms. We cover topics such as choosing an appropriate significance test for the major NLP tasks, dealing with the unique aspects of significance testing for non-convex deep neural networks, accounting for a large number of comparisons between two NLP algorithms in a statistically valid manner (multiple hypothesis testing), and, finally, the unique challenges yielded by the nature of the data and practices of the field.

Statistical Methods

Author : Rudolf J. Freund
Publisher : Elsevier
ISBN 13 : 0080498221
Total Pages : 694 pages
Book Rating : 4.0/5 (84 download)

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Book Synopsis Statistical Methods by : Rudolf J. Freund

Download or read book Statistical Methods written by Rudolf J. Freund and published by Elsevier. This book was released on 2003-01-07 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: This broad text provides a complete overview of most standard statistical methods, including multiple regression, analysis of variance, experimental design, and sampling techniques. Assuming a background of only two years of high school algebra, this book teaches intelligent data analysis and covers the principles of good data collection. * Provides a complete discussion of analysis of data including estimation, diagnostics, and remedial actions * Examples contain graphical illustration for ease of interpretation * Intended for use with almost any statistical software * Examples are worked to a logical conclusion, including interpretation of results * A complete Instructor's Manual is available to adopters

Small Clinical Trials

Author : Institute of Medicine
Publisher : National Academies Press
ISBN 13 : 0309171148
Total Pages : 221 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Small Clinical Trials by : Institute of Medicine

Download or read book Small Clinical Trials written by Institute of Medicine and published by National Academies Press. This book was released on 2001-01-01 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clinical trials are used to elucidate the most appropriate preventive, diagnostic, or treatment options for individuals with a given medical condition. Perhaps the most essential feature of a clinical trial is that it aims to use results based on a limited sample of research participants to see if the intervention is safe and effective or if it is comparable to a comparison treatment. Sample size is a crucial component of any clinical trial. A trial with a small number of research participants is more prone to variability and carries a considerable risk of failing to demonstrate the effectiveness of a given intervention when one really is present. This may occur in phase I (safety and pharmacologic profiles), II (pilot efficacy evaluation), and III (extensive assessment of safety and efficacy) trials. Although phase I and II studies may have smaller sample sizes, they usually have adequate statistical power, which is the committee's definition of a "large" trial. Sometimes a trial with eight participants may have adequate statistical power, statistical power being the probability of rejecting the null hypothesis when the hypothesis is false. Small Clinical Trials assesses the current methodologies and the appropriate situations for the conduct of clinical trials with small sample sizes. This report assesses the published literature on various strategies such as (1) meta-analysis to combine disparate information from several studies including Bayesian techniques as in the confidence profile method and (2) other alternatives such as assessing therapeutic results in a single treated population (e.g., astronauts) by sequentially measuring whether the intervention is falling above or below a preestablished probability outcome range and meeting predesigned specifications as opposed to incremental improvement.