Applied Statistical Methods
Learn fundamental concepts and methods needed
to organize and analyze data to make objective decisions.
The course instructs in the development of mathematical models
to predict outcomes and understand key factors affecting processes.
Knowledge of basic algebra is helpful. Note: computers will
be used in class to apply learned techniques. Please bring
a laptop if possible.
Seminar Content
Characterizing a Single Process
- Estimation of a Mean, Variance and Proportion
- Detecting Outliers
- Confidence Intervals for the Estimates
- Type I and II Errors
- Hypothesis Testing for the Mean, Variance
and Proportion
- Paired Data and the Paired t Test
Comparison of Two Processes
- Testing for Equal Means
- Testing for Equal Variances
- Testing for Equal Proportions
Comparison of Multiple Processes
- ANOVA for Comparing Means
- Confidence Intervals for Multiple Comparisons
Describing the Relationship between
Two Variables
- Correlation
- Simple Linear Regression
- R Squared
- Residual Analysis
- Confidence and Prediction Intervals
Predicting a Response Using Several
Variables
- Multiple Regression
- Testing for Significant Explanatory Variables
- Model Selection
Who Should
Attend
Individuals involved with analysis of process data underlying
quality and productivity improvement.
Prerequisites
A knowledge of basic algebra is highly recommended. Computer
analysis using Microsoft ExcelTM and StatgraphicsTM will be
emphasized.
Related Seminars
Statistical Process Control II
Design of Experiments II
Seminar
Fee: $795
All meals, excluding dinner, are included.
Each participant will receive a comprehensive
manual and a Certificate of Completion at the close of the
seminar.
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