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Minitab Training

Author: art_links Date: 3-11-2017, 00:07 Comments: 0 Views: 14
Minitab Training
Minitab Training
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1.5 Hours | Lec: 33 | 163 MB
Genre: eLearning | Language: English

This course is well suited for instructional applications

Minitab is used for; a) Data and File Management "spreadsheet for better data analysis", b) Regression Analysis, c) Power and Sample Size, d) Tables and Graphs, e) Multivariate Analysis "includes factor analysis", f) cluster analysis, g) correspondence analysis, h) Non para-metrics "various tests including sign test", i) runs test, j) Friedman test, k) Time Series and Forecasting "tools that help show trends in data as well as predicting future values", l) Time series Descriptions, m) exponential smoothing, n) trend analysis, o) Statistical Process Control, p) Measurement System Analysis, q) Analysis of Variance "to determine the difference between data points".

This course is well suited for instructional applications
Minitab is a general-purpose statistical software package designed for easy interactive use. It was originally developed at the Pennsylvania State University by researchers Barbara F. Ryan, Thomas A. Ryan, Jr., and Brian L. Joiner in 1972. Minitab is well suited for instructional applications, but is also powerful enough to be used as a primary tool for analyzing research data. Minitab is commonly used in Six Sigma, particularly in the Measure and Analyse phases of DMAIC. Minitab provides a quick, effective solution for the level of analysis required in most Six Sigma projects.
Minitab is used for; a) Data and File Management "spreadsheet for better data analysis", b) Regression Analysis, c) Power and Sample Size, d) Tables and Graphs, e) Multivariate Analysis "includes factor analysis", f) cluster analysis, g) correspondence analysis, h) Non para-metrics "various tests including sign test", i) runs test, j) Friedman test, k) Time Series and Forecasting "tools that help show trends in data as well as predicting future values", l) Time series Descriptions, m) exponential smoothing, n) trend analysis, o) Statistical Process Control, p) Measurement System Analysis, q) Analysis of Variance "to determine the difference between data points".

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