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Engineering Statistics and Data Analysis (ESDA) |
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3 days |
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- Course Description and Audience:
- ESDA is for Engineers, Scientists and Managers who routinely analyze data for product development, qualification and control. Areas of focus are; analysis of data for basic product development and manufacturing applications including foundation statistics, distribution analysis, capability assessment, sensitivity prediction, comparison tests, sample size selection and model fitting.
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On-Site Course
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- Currently Available
- To request this course for on-site training, please click here.
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Public Course
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- Currently Available
- To view a list of available public courses, click here.
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- Course Objectives:
- Upon completion of the course the participants will be able to:
- 1. Understand the ideas associated with sampling and data collection.
- 2. Demonstrate the ability to evaluate distributions.
- 3. Select appropriate sample sizes for performance evaluation.
- 4. Conduct comparative tests using data.
- 5. Use regression techniques in order to analyze the results and make process/product improvements.
- 6. Select an appropriate analysis technique based on the type of data.
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- Software:
- JMP or Minitab
- Prerequisites:
- None
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Section I |
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- Introduction to JMP or Minitab
- Table Commands
- Column Commands
- Row Commands
- Subset, Stack and Join Commands
- Saving Data and Graphs
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| Section II |
- Statistics Foundations & Distribution Analysis
- Measures of Center and Spread
- Standard Error and Central Limit Theorem
- Normal Distribution, T Distribution and Confidence Intervals
- Test for Normality
- Data and Tolerance Intervals (normal)
- Process Capability (normal) and Non-normal Distribution Fitting
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| Section III |
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- Nominal X, Continuous Y
- Contour Plots, Components of Variance and REML
- Sample Size for the Mean and Standard Deviation
T Test - One Sample, Two Sample and Paired
Test for Differences in Variances
One-way ANOVA and N Way ANOVA
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| Section IV |
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- Continuous X, Continuous Y
- Simple Linear Regression, Correlation
Multiple Regression and ANCOVA
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| Section V |
- Nominal X, Nominal Y
- Mean and Sigma for Proportion Defective
- Sample Size and Statistical Tests for Proportion Defective
- Mean and Sigma for Defect per Unit
- Chi-Square Test for Defects and Proportion Defective
- Pareto Graphs and Cross Tabs Analysis
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| Section VI |
- Continuous X and Nominal Y
- Logistic Regression
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