Information
• Minitab is the world's leading software for statistics education, packed with
features that clarify concepts and simplify learning.
• Thousands of companies use software, so learning with Minitab also gives students
valuable experience with real-world business tools.
• Minitab Statistical Software is the leading package used by businesses to analyze
quality improvement data.
• More than 4,000 colleges and universities also use it to teach statistics. Companies
worldwide use Quality Companion to manage their improvement projects.
• Minitab is a powerful software for identifying the defects, quality and business
improvements. Minitab gives you the tools you need to analyze your data and make
informed decisions about how to improve your business.
• Its power & ease of use make it the leading packages worldwide. Upgradation of
skill to work towards business analysis operational excellence, Course will prepare
candidates for analyzing complex data.
Course Content
-
Plot Interpretation using Minitab
|
Graphs including histograms, plots, boxplots, bar charts,interval plot, and time
series plots.
|
-
Descriptive Statistics
• Fundamentals of statistics (Mean, Median, mode)
• Basic statistics, measures of Centre and Spread
• Assess normality of your data
• Confidence intervals.
|
-
Statistical Quality tools
• Understand measurement systems (Gage R&R, Linearity and Stability)
• Process stability (variable and attribute control charts)
• Process capability (for normal, and binomial data)
-
Design of Experiments
• Understand and analyze full and fractional factorial designs using MINITAB’s intuitive
DOE .
• Learn to interpret Pareto charts, normal plots of effects, cube, main effects,
and interaction plots in combination with tabulated statistical output and the response
optimizer.
• Choose settings that optimize one or more responses or determine the direction
of further experimentation
|
-
Advanced Statistical Plots
• Understand potential relationship between variables using correlation, regression
and matrix plots.
• Use t-tests, ANOVA and variance tests to show evidence of a process change or
improvement
|
-
Regression
• Understand potential relationship between variables using correlation, regression
and matrix plots.
|
• Regression
|
• Best Subsets
|
|
• Stepwise
|
• Fitted Line Plot
|
|
• PLS
|
• Binary Logistic
|
|
• Ordinal Logistic
|
• Nominal Logistic
|
-
ANOVA
A one-way analysis of variance (ANOVA) tests the hypothesis that the means of several
populations are equal.
|
• One-way ANOVA
|
• Two-way ANOVA
|
|
• Analysis of Means
|
• GLM
|
|
• Balanced ANOVA
|
• Fully nested ANOVA
|
|
• MANOVA
|
• Test of Equal Variances
|
-
Control Charts
Plots your process data in time-ordered sequence to help identify common cause and
special cause variation.
|
• Box-Cox Transformation
|
• Variable Charts for Subgroups
|
|
• Variable Charts for Individuals
|
• Attributes Charts
|
|
• Time-Weighted Charts
|
• Multivariate Charts
|
Minitab also offers time weighted control charts and multivariate control charts
for more complex applications
-
Reliability
• The proportion of units that survive beyond a given time.
• These estimates of survival probabilities are often referred to as reliability
estimates.
• Use these values to determine whether your product meets reliability requirements
or to compare the reliability of two or more designs of a product.
|
-
Multivariate
|
• Principal Components
|
• Factor Analysis
|
|
• Cluster Observations
|
• Cluster Variables
|
|
• Cluster K-Means
|
• Discriminant Analysis
|
|
• Simple Correspondence Analysis
|
• Multiple Correspondence Analysis
|
-
Time Series
|
• Trend Analysis
|
• Decomposition
|
|
• Moving Average
|
• Single Exponential Smoothing
|
|
• Double Exponential Smoothing
|
• Winters' Method
|
|
• Differences and Lag
|
• Autocorrelation
|
|
• ARIMA
|