Minitab Student Handbook
Author : Thomas Arthur Ryan
Publisher : Brooks/Cole
Page : 356 pages
File Size : 10,81 MB
Release : 1976
Category : Computers
ISBN :
The Student Guide to Minitab Release 14
Author : John McKenzie
Publisher : Addison-Wesley Longman
Page : 0 pages
File Size : 21,85 MB
Release : 2004
Category : Biometry
ISBN : 9780321113122
Book Description
The Guide to Minitab includes both a Getting Started with Minitab section and hands-on, self-paced Tutorials designed to teach students how to use the software capabilities through a variety of approaches. The Tutorials cover all of the primary features and capabilities of MINITAB, including graphical and numerical methods for one and two or more variables, bivariate analysis, total quality management tools, time series analysis, and taking data from the web, to name a few. MINITAB is an easy-to-use general-purpose statistical computing package for analyzing data. It is a flexible and powerful tool that was designed from the beginning to be used by students and researchers new to statistics. It is now one of the most widely used statistics packages in the world. Minitab performs horribly tedious computations and produces accurate and professional quality graphs almost instantly. This power frees the user to focus on the exploration of the structure of the data and the interpretation of the output. MINITAB software not included.
Problem Solving and Data Analysis Using Minitab
Author : Rehman M. Khan
Publisher : John Wiley & Sons
Page : 715 pages
File Size : 44,33 MB
Release : 2013-01-28
Category : Mathematics
ISBN : 1118307526
Book Description
Six Sigma statistical methodology using Minitab Problem Solving and Data Analysis using Minitab presents example-based learning to aid readers in understanding how to use MINITAB 16 for statistical analysis and problem solving. Each example and exercise is broken down into the exact steps that must be followed in order to take the reader through key learning points and work through complex analyses. Exercises are featured at the end of each example so that the reader can be assured that they have understood the key learning points. Key features: Provides readers with a step by step guide to problem solving and statistical analysis using Minitab 16 which is also compatible with version 15. Includes fully worked examples with graphics showing menu selections and Minitab outputs. Uses example based learning that the reader can work through at their pace. Contains hundreds of screenshots to aid the reader, along with explanations of the statistics being performed and interpretation of results. Presents the core statistical techniques used by Six Sigma Black Belts. Contains examples, exercises and solutions throughout, and is supported by an accompanying website featuring the numerous example data sets. Making Six Sigma statistical methodology accessible to beginners, this book is aimed at numerical professionals, students or academics who wish to learn and apply statistical techniques for problem solving, process improvement or data analysis whilst keeping mathematical theory to a minimum.
A Minitab Guide to Statistics
Author : Ruth K. Meyer
Publisher :
Page : 436 pages
File Size : 40,50 MB
Release : 2001
Category : Business & Economics
ISBN : 9780130141569
Book Description
Disk contains: Appendix -- Example data files -- Exercises.
Quantitative Data Analysis with Minitab
Author : Alan Bryman
Publisher : Routledge
Page : 308 pages
File Size : 11,52 MB
Release : 2003-09-02
Category : Psychology
ISBN : 113480573X
Book Description
Quantitative data analysis is now a compulsory component of most degree courses in the social sciences and students are increasingly reliant on computers for the analysis of data. Quantitative Data Analysis with Minitab explains statistical tests for Minitab users using the same formulae free, non technical approach, as the very successful SPPS version. Students will learn a wide range of quantitative data analysis techniques and become familiar with how these techniques can be implemented through the latest version of Minitab. Techniques covered include univariate analysis (with frequency table, dispersion and histograms), bivariate (with contingency tables correlation, analysis of varience and non-parametric tests) and multivariate analysis (with multiple regression, path analysis, covarience and factor analysis). In addition the book covers issues such as sampling, statistical significance, conceptualisation and measurement and the selection of appropriate tests. Each chapter concludes with a set of exercises. Social science students will welcome this integrated, non mathematical introduction to quantitative data anlysis and the minitab package.
Lean Six SIGMA and Minitab
Author : Quentin Brook
Publisher :
Page : 314 pages
File Size : 50,90 MB
Release :
Category :
ISBN : 9780995789920
Book Description
Minitab Demystified
Author : Andrew Sleeper
Publisher : McGraw Hill Professional
Page : 576 pages
File Size : 22,29 MB
Release : 2011-08-22
Category : Business & Economics
ISBN : 0071762302
Book Description
Need to learn Minitab? Problem Solved! Get started using Minitab right way with help from this hands-on guide. Minitab Demystified walks you through essential Minitab features and shows you how to apply them to solve statistical analysis problems. Featuring coverage of Minitab 16, this practical guide explores the Minitab interface and the full range of Minitab graphics, Distribution models, statistical intervals, hypothesis testing, and sample size calculations are clearly explained. The book covers modeling tools of regression and the design of experiments (DOE) as well as the industrial quality tools of measurement systems analysis, control charts, capability analysis, acceptance sampling, and reliability analysis. Detailed examples and concise explanations make it easy to understand the material, and end-of-chapter quizzes and a final exam help reinforce key concepts. It's a no-brainer! You'll learn about: Accessing powerful Minitab functions with the Minitab assistant Confidence, prediction, and tolerance intervals Designing and analyzing experiments with hard-to-change variables Statistical process control (SPC), Six Sigma applications, and quality control Predicting the economic impact of sampling Analyzing life data with additional variables Simple enough for a beginner, challenging enough for an advanced student, and thorough enough for a Six Sigma professional, Minitab Demystified is your shortcut to statistical analysis success!
Statistical Quality Control
Author : Bhisham C. Gupta
Publisher : John Wiley & Sons
Page : 400 pages
File Size : 49,52 MB
Release : 2021-07-23
Category : Technology & Engineering
ISBN : 1119671728
Book Description
STATISTICAL QUALITY CONTROL Provides a basic understanding of statistical quality control (SQC) and demonstrates how to apply the techniques of SQC to improve the quality of products in various sectors This book introduces Statistical Quality Control and the elements of Six Sigma Methodology, illustrating the widespread applications that both have for a multitude of areas, including manufacturing, finance, transportation, and more. It places emphasis on both the theory and application of various SQC techniques and offers a large number of examples using data encountered in real life situations to support each theoretical concept. Statistical Quality Control: Using MINITAB, R, JMP and Python begins with a brief discussion of the different types of data encountered in various fields of statistical applications and introduces graphical and numerical tools needed to conduct preliminary analysis of the data. It then discusses the basic concept of statistical quality control (SQC) and Six Sigma Methodology and examines the different types of sampling methods encountered when sampling schemes are used to study certain populations. The book also covers Phase 1 Control Charts for variables and attributes; Phase II Control Charts to detect small shifts; the various types of Process Capability Indices (CPI); certain aspects of Measurement System Analysis (MSA); various aspects of PRE-control; and more. This helpful guide also Focuses on the learning and understanding of statistical quality control for second and third year undergraduates and practitioners in the field Discusses aspects of Six Sigma Methodology Teaches readers to use MINITAB, R, JMP and Python to create and analyze charts Requires no previous knowledge of statistical theory Is supplemented by an instructor-only book companion site featuring data sets and a solutions manual to all problems, as well as a student book companion site that includes data sets and a solutions manual to all odd-numbered problems Statistical Quality Control: Using MINITAB, R, JMP and Python is an excellent book for students studying engineering, statistics, management studies, and other related fields and who are interested in learning various techniques of statistical quality control. It also serves as a desk reference for practitioners who work to improve quality in various sectors, such as manufacturing, service, transportation, medical, oil, and financial institutions. It‘s also useful for those who use Six Sigma techniques to improve the quality of products in such areas.
Statistics and Probability with Applications for Engineers and Scientists
Author : Bhisham C. Gupta
Publisher : John Wiley & Sons
Page : 896 pages
File Size : 25,67 MB
Release : 2013-04-29
Category : Mathematics
ISBN : 1118464044
Book Description
Introducing the tools of statistics and probability from the ground up An understanding of statistical tools is essential for engineers and scientists who often need to deal with data analysis over the course of their work. Statistics and Probability with Applications for Engineers and Scientists walks readers through a wide range of popular statistical techniques, explaining step-by-step how to generate, analyze, and interpret data for diverse applications in engineering and the natural sciences. Unique among books of this kind, Statistics and Probability with Applications for Engineers and Scientists covers descriptive statistics first, then goes on to discuss the fundamentals of probability theory. Along with case studies, examples, and real-world data sets, the book incorporates clear instructions on how to use the statistical packages Minitab® and Microsoft® Office Excel® to analyze various data sets. The book also features: • Detailed discussions on sampling distributions, statistical estimation of population parameters, hypothesis testing, reliability theory, statistical quality control including Phase I and Phase II control charts, and process capability indices • A clear presentation of nonparametric methods and simple and multiple linear regression methods, as well as a brief discussion on logistic regression method • Comprehensive guidance on the design of experiments, including randomized block designs, one- and two-way layout designs, Latin square designs, random effects and mixed effects models, factorial and fractional factorial designs, and response surface methodology • A companion website containing data sets for Minitab and Microsoft Office Excel, as well as JMP ® routines and results Assuming no background in probability and statistics, Statistics and Probability with Applications for Engineers and Scientists features a unique, yet tried-and-true, approach that is ideal for all undergraduate students as well as statistical practitioners who analyze and illustrate real-world data in engineering and the natural sciences.
Applied Statistics for Engineers and Scientists
Author : David M. Levine
Publisher : Pearson
Page : 746 pages
File Size : 45,14 MB
Release : 2001
Category : Business & Economics
ISBN :
Book Description
For courses in Probability and Statistics. This applied text for engineers and scientists, written in a non-theoretical manner, focuses on underlying principles that are important to students in a wide range of disciplines. It emphasizes the interpretation of results, the presentation and evaluation of assumptions, and the discussion of what should be done if the assumptions are violated. Integration of spreadsheet and statistical software (Microsoft Excel and Minitab) as well as in-depth coverage of quality and experimental design complete this treatment of statistics.
