Normality Testing in Excel - The Excel Statistical Master PDF Download
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Author: Mark Harmon
Publisher: Mark Harmon
ISBN: 0983307059
Category : Business & Economics
Languages : en
Pages : 54
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Book Description
50 pages of complete step-by-step instructions showing how to perform a number of well-known Normality tests and how to do them all in Excel. This e-manual will make you an expert on knowing exactly how and when to use these types of Normality tests: the Histogram, the Normal Probability Plot using 2 different methods, and the Chi-Square Goodness-Of-Fit Test, and how to set them all up in Excel. This e-manual is loaded with completed problems and step-by-step, easy-to-follow screenshots in Excel of all these different types of Normality tests. The instructions are clear and easy-to-follow but at the graduate level. If you are currently taking a difficult graduate-level statistics course that covers Normality testing, you will find this e-manual to be an outstanding course supplement that will explain Normality tests much more clearly than your textbook does. If you are a business manager, you will really appreciate how easily and clearly this e-manual will show you how you can perform these useful and quick Normality tests in Excel to verify data distributions on your job. Normality testing should always be performed before any of the widely-used parametric statistical tests are applied to data. Not many know how to do Normality testing. This e-manual will make you an Excel Statistical Master of Normality testing.
Author: Mark Harmon
Publisher: Mark Harmon
ISBN: 0983307059
Category : Business & Economics
Languages : en
Pages : 54
Get Book Here
Book Description
50 pages of complete step-by-step instructions showing how to perform a number of well-known Normality tests and how to do them all in Excel. This e-manual will make you an expert on knowing exactly how and when to use these types of Normality tests: the Histogram, the Normal Probability Plot using 2 different methods, and the Chi-Square Goodness-Of-Fit Test, and how to set them all up in Excel. This e-manual is loaded with completed problems and step-by-step, easy-to-follow screenshots in Excel of all these different types of Normality tests. The instructions are clear and easy-to-follow but at the graduate level. If you are currently taking a difficult graduate-level statistics course that covers Normality testing, you will find this e-manual to be an outstanding course supplement that will explain Normality tests much more clearly than your textbook does. If you are a business manager, you will really appreciate how easily and clearly this e-manual will show you how you can perform these useful and quick Normality tests in Excel to verify data distributions on your job. Normality testing should always be performed before any of the widely-used parametric statistical tests are applied to data. Not many know how to do Normality testing. This e-manual will make you an Excel Statistical Master of Normality testing.
Author: Mark Harmon
Publisher: Mark Harmon
ISBN: 0983307083
Category : Computers
Languages : en
Pages : 478
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Book Description
Complete and practical yet easy-to-understand graduate-level statistics course with all of the problems worked out in Excel. Thoroughly covers all topics of an intense graduate statistics course using nothing but step-by-step, simple explanations. Loaded with completed, real-world problems all in Excel, this e-manual is an outstanding supplement to a graduate statistics course. Very clear explanations are used to show exactly how the Excel formulas integrate with the statistical frameworks being applied. The reader will learn how to master and apply graduate-level statistics much faster than a student in a normal graduate statistics course because this e-manual's emphasis is entirely on problem solving, not on useless, forgettable theory that fills up many statistics courses. This e-manual achieves two goals: teaching graduate-level statistical frameworks in an easy-to-understand way and then showing how to implement all of it in Excel. The widely-used Microsoft Excel program provides a very simple but incredibly complete platform to perform heavy-duty, advanced statistical analysis. All other statistical software packages, such as Minitab, SyStat, and SPSS, are expensive, require lots of user training, and expect that the user is an expert statistician right from the start. Not this e-manual nor Microsoft Excel. The ability to perform graduate-level statistics in Excel is an extremely useful and powerful tool for any graduate statistics student and business manager. Homework assignments can be quickly checked with Excel. Once difficult statistical business problems are now readily solvable in Excel. The easy-to-follow frameworks in this e-manual can be cleanly and swiftly duplicated in the real world and on statistics exams by hand (without Excel) right away. The lessons are all in bite-size chunks that are quickly absorbed for immediate use. More than half of the lessons in this e-manual are supplemented with step-by-step videos for more convenient learning. Some of the major topics covered in detail include regression, ANOVA, hypothesis tests, confidence intervals, combinations, permutations, correlation, covariance, t-tests, histograms, and charting. This e-manual also contains two complete chapters with numerous videos showing exactly how to create user-interactive graphs of the 10 major distributions in Excel. These user-interactive Excel graphs allow the user to vary the cells containing all of the distribution's parameters, such as mean, standard deviation, and degrees of freedom, and watch the graphed distribution instantly change right on the spreadsheet to conform to the new parameters. This is an excellent and unique tool to fully grasp the functionality of the distributions discussed in this e-manual. All problem-solving techniques are presented as step-by-step frameworks that can be readily applied to similar problems, not as seemingly unrelated and difficult-to-apply statistical theorems like most statistics course do. A number of problem-solving techniques are presented in this e-manual that do not appear in any other statistical text. One example of a statistical technique presented only in this e-manual and nowhere else is a detailed description showing how to solve every type of hypothesis test using the same four steps. A number of widely-used and complicated statistical tests, such as the chi-square independence test, the chi-square population variance test, and conjoint analysis using dummy variable regression are described from top to bottom and also in Excel. Graduate statistics students and business managers will find this e-manual to be, by far, the easiest and fastest way to master graduate-level statistics and to apply advanced statistics in Excel to solve difficult, real-world problems, homework assignments, and exam questions. The reader of this e-manual will quickly become an Excel Statistical Master.
Author: Mark Harmon
Publisher: Mark Harmon
ISBN: 0983307032
Category : Business & Economics
Languages : en
Pages : 62
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Book Description
56 pages of clear and simple yet complete instructions about what t-tests are, how and when to use them, and how to set them up and solve them in Excel. This e-manual provides a thorough explanation of all of the major types of t-tests and their underlying formulas. Before you even begin to solve t-tests in Excel, the e-manual ensures that you have a solid, intuitive grasp of what each of the different variations of t-tests do and when each should be used. The e-manual shows you how to do these t-tests by hand and also in Excel. All of the t-tests formulas and functions built-in to Excel are explained in deep detail. All of problems are solved using the built-in Excel t-tests with lots of screenshots for complete clarity. A number of the problems also have their t-values and p-values calculated by hand so you can also see how it would be done manually. The instructions are clear and easy-to-follow but at the graduate level. If you are currently taking a difficult graduate-level statistics course that covers t-tests, you will find this e-manual to be an outstanding course supplement that will explain t-tests much more clearly than your textbook does. If you are a business manager, you will really appreciate how easily and clearly this e-manual will show you how you can set up t-tests in Excel to solve difficult statistical problems on your job. This e-manual will make you an Excel Statistical Master of the t-test.
Author: Mark Harmon
Publisher: Mark Harmon
ISBN: 0983307040
Category : Business & Economics
Languages : en
Pages : 72
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Book Description
69 pages of complete step-by-step instructions showing how to perform nearly every major type of nonparametric test and how to do them all in Excel. This e-manual will make you an expert on knowing exactly how and when to use and set up in Excel all types of nonparametric tests, such as the Mann Whitney U Test, the Kruskall Wallis Test, the Wilcoxon Rank Sum Test for both large and small samples, the Spearman Correlation Coefficient Test, the Sign Test, and the Wilcoxon Signed Rank Test for both large and small samples. This e-manual is loaded with completed examples and screenshots in Excel of all the above of nonparametric tests being performed. The instructions are clear and easy-to-follow but at the graduate level. If you are currently taking a difficult graduate-level statistics course that covers nonparametric or normality tests, you will find this e-manual to be an outstanding course supplement that will explain nonparametric tests much more clearly than your textbook does. If you are a business manager, you will really appreciate how easily and clearly this e-manual will show you how you can perform nonparametric tests in Excel to solve difficult statistical problems on your job. Nonparametric tests are the most important of all statistical tests in business, but are not widely understood. Nonparametric testing must nearly always be performed in place of most well-known statistics tests when it is not known that samples are being taken from a normally distributed population. This is more often the case than not, yet not many people have a working knowledge of nonparametric testing. You will. This e-manual will make you an Excel Statistical Master of nonparametric testing.
Author: J. P. Verma
Publisher: John Wiley & Sons
ISBN: 1118855175
Category : Mathematics
Languages : en
Pages : 1227
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Book Description
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
Author: J. P. Verma
Publisher: John Wiley & Sons
ISBN: 1119528410
Category : Mathematics
Languages : en
Pages : 224
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Book Description
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.
Author: Ramalingam Shanmugam
Publisher: Cambridge University Press
ISBN: 100921201X
Category : Medical
Languages : en
Pages : 529
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Book Description
This book effectively exposes and illustrates the ideas and tools for optimal healthcare decisions taken from evidence.
Author: Loon Ching Tang
Publisher: John Wiley & Sons
ISBN: 0470061995
Category : Technology & Engineering
Languages : en
Pages : 426
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Book Description
The 2007 winner of the Masing Book Prize sets out important Six Sigma concepts and a selection of up-to-date tools for quality improvement in industry. Six Sigma is a widely used methodology for measuring and improving an organization’s operational performance through a rigorous analysis of its practices and systems. This book presents a series of papers providing a systematic ‘roadmap’ for implementing Six Sigma, following the DMAIC (Define, Measure, Analyse, Improve and Control) phased approach. Motivated by actual problems, the authors offer insightful solutions to some of the most commonly encountered issues in Six Sigma projects, such as validation of normality, experimentation under constraints and statistical control of complex processes. They also include many examples and case studies to help readers learn how to apply the appropriate techniques to real-world problems. Key features: Provides a comprehensive introduction to Six Sigma, with a critical strategic assessment and a SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis. Presents some prominent design features of Six Sigma, and a newly proposed roadmap for healthcare delivery. Sets out information on graphical tools, including fishbone diagrams, mind-maps, and reality trees. Gives a thorough treatment of process capability analysis for non-normal data. Discusses advanced tools for Six Sigma, such as statistical process control for autocorrelated data. Consolidating valuable methodologies for process optimization and quality improvement, Six Sigma: Advanced Tools for Black Belts and Master Black Belts is a unique reference for practising engineers in the electronics, defence, communications and energy industries. It is also useful for graduate students taking courses in quality assurance.
Author: Herschel Knapp
Publisher: SAGE Publications
ISBN: 1506358705
Category : Social Science
Languages : en
Pages : 313
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Book Description
The updated Second Edition of Herschel Knapp’s friendly and practical introduction to statistics shows students how to properly select, process, and interpret statistics without heavy emphasis on theory, formula derivations, or abstract mathematical concepts. Each chapter is structured to answer questions that students most want answered: What statistical test should I use for this situation? How do I set up the data? How do I run the test? How do I interpret and document the results? Online tutorial videos, examples, screenshots, and intuitive illustrations help students "get the story" from their data as they learn by doing, completing practice exercises at the end of each chapter using prepared downloadable data sets.
Author: MrExcel's Holy Macro! Books
Publisher: Packt Publishing Ltd
ISBN: 1837029725
Category : Computers
Languages : en
Pages : 321
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Book Description
Master data visualization, statistical tools, and regression analysis tailored for scientific research in Excel 2013. Discover tools to streamline experiments and improve productivity. Key Features Comprehensive guide to Excel 2013 tools tailored for scientific data analysis and modeling Practical examples and exercises designed specifically for research and experimental workflows Detailed coverage of statistical methods, regression techniques, and advanced graphing tools Book DescriptionThis book provides a detailed guide for scientists to fully utilize Excel 2013 for data analysis, visualization, and statistical modeling. It begins with core spreadsheet techniques like range names, nested functions, and cell referencing, creating a strong foundation for advanced skills. Tailored examples help readers understand how to apply these basics in scientific contexts. The book progresses into advanced data analysis tools, covering pivot tables, lookups, conditional formatting, and filtering techniques. Regression methods, curve fitting, and distribution simulations are explored, allowing readers to analyze trends, predict outcomes, and validate data. Statistical methods such as ANOVA, significance testing, and sampling techniques are presented with practical examples to reinforce learning. Later chapters focus on advanced graphing techniques, customizing charts, and working with complex functions like arrays and nonlinear regression. Exercises and step-by-step instructions ensure concepts are clear and practical. By the end, readers will confidently apply Excel tools to streamline experiments, enhance productivity, and achieve scientific precision.What you will learn Create tailored graphs and charts for scientific research needs Analyze complex datasets with advanced Excel 2013 functions Utilize pivot tables for efficient frequency distribution analysis Generate random data samples for simulation and experiments Differentiate key statistical functions for precise calculations Automate data validation and formatting to enhance accuracy Who this book is for Students and professionals in science, engineering, and related fields seeking practical Excel skills will find this book helpful. Basic familiarity with Excel is recommended. No advanced programming or statistical background is required.
