Download Applied Statistics for the Six Sigma Green Belt by Bhisham C. Gupta PDF
By Bhisham C. Gupta
This publication is a table reference for 6 Sigma eco-friendly belts or newbies who're no longer acquainted with facts. As Six Sigma staff individuals, eco-friendly belts may also help pick out, acquire facts for, and help with the translation of quite a few statistical or quantitative instruments in the context of the Six Sigma method. This e-book will function an outstanding educational device constructing a powerful realizing of easy records together with the way to describe info either graphically and numerically. It’s particular concentration is on innovations, functions, and interpretations of the statistical instruments used in the course of, and as a part of, the layout, degree, study, increase, and regulate (DMAIC) technique. in contrast to so much books for 6 Sigma newbies, this ebook isn't just a proof of Six Sigma, it bargains genuine instruments and theories to aid practitioners larger comprehend and practice their jobs in gathering and reading info. Readers utilizing this e-book will discover ways to comprehend the advantages of information as an aim degree, in addition to the method of utilizing chosen instruments for interpreting facts and the way to make judgements in response to quantitative inputs.
record of Figures
checklist of Tables
desk of Contents
1. environment the Context for 6 Sigma
2. Getting began with data
three. Describing info Graphically
four. Describing facts Numerically
6. Discrete Random Variables and Their chance Distributions
7. non-stop Random Variables and Their likelihood Distributions
eight. Sampling Distributions
nine. aspect and period Estimation
10. speculation trying out
eleven. computing device assets to help utilized statistics: utilizing MINITAB® and JMP® Statistical software program
concerning the Authors
Contents of CD-ROM
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Additional resources for Applied Statistics for the Six Sigma Green Belt
DESCRIPTION USE Provides a visual display of qualitative data. It is also used to compare two or more sets of qualitative data. TYPE OF DATA Categorical (qualitative) data. DESIGN/APPLICATION CONSIDERATIONS Units used in each category must be identical. For example, comparing parts manufactured by different companies must have identical specifications. Categories must be isolated from each other. SPECIAL COMMENTS/CONCERNS A bar chart can be presented vertically or horizontally. It differs from the Pie Chart in the sense that it can be used to compare two or more populations whereas the Pie Chart can be used only to study one population.
34, respectively. 2 Variance One of the most interesting pieces of information associated with any data is how the values in the data set vary from one another. Of course, range can give us some idea of variability. Unfortunately, range does not help us understand centrality. To better understand variability, we rely on more powerful 54 Chapter Four indicators such as variance, which is a value that focuses on how much individual observations within the data set deviate from their mean. For example, if the values in the data set are x1, x2, x3, ...
Remember, the total angle of the circle is 360 degrees. The angle of a slice corresponding to a given category is determined as follows: Angle of a slice ϭ (Relative frequency of the given category) ϫ 360. 5. 5 In a manufacturing operation we are interested in better understanding defect rates as a function of our various process steps. The inspection points are initial cutoff, turning, drilling, and assembly. 6. Construct a pie chart for these data. Solution: The pie chart for these data is constructed by dividing the circle into four slices.