## Introduction to Statistical Methods for Managers

### Purpose

This course provides individuals in decision-making positions with a basic understanding of data collection and description, inferences about processes and populations based upon samples, and the design of appropriate experiments. Emphasis in this course is placed on the understanding of statistical methods and concepts, as well as the uses and importance of these methods. The interpretation of the results of statistical analyses are explored in-depth. Special emphasis in the area of the design of industrial research is placed upon risk (Type I and II errors), sample sizes, the implications of the use of discrete versus continuous data, sampling techniques, and their relationship to the conduct of reliable and valid industrial research.

4 days

No limit

None

### Primary Resource Materials

Statistical Methods for Managers Manual

### Content Outline

• Basic Statistical Theory
• Frequency Distributions
• Basic Descriptive Statistics
• Probability and Probability Distributions
• Introduction to Probability
• Theoretical Probability Distributions
• The Binomial Distribution
• The Poisson Distribution
• The Normal and Log-Normal Distribution
• The Exponential Distribution
• The Weibull Distribution
• Sampling and Estimation
• Sampling and Random Sampling Distributions
• Point and Interval Estimation: An Introduction
• An Overview of Statistical Decision-Making Techniques and Tools
• An Introduction to Hypothesis Testing
• Significance, Importance, Confidence, Power, and Risk
• Process Control Charts
• Capability Analyses: Short and Long-Term Methods and Considerations

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## Practicum in Statistical Quality Control

### Purpose

This seminar provides an opportunity to apply statistical skills acquired in earlier courses. Participants learn to synthesize and evaluate the results of research and data gathering efforts as intelligent researchers, presenters, and consumers of data; and ask correct and appropriate questions, make appropriate observations, and suggest sensible follow-up strategies when presented with the results of industrial research. Participants conduct analyses for case studies with actual data collected in the past from both the customer and vendor perspective and from actual plant/engineering research studies.

4 days

### Number of Participants

30 participants maximum

### Prerequisites

Introduction to Statistical Process Control and Capability, Advanced Statistical Process Control and Capability, Experimental Design and Industrial Statistics (Levels I through III)

### Primary Resource Materials

Practicum in Statistical Quality Control manual

### Content Outline

Case Studies for Participant Analyses

1. Improving Incoming Material for Our Can Plant Customers
2. Analyzing Steam Line Performance on an EMC Casting Pit
3. Analyzing the Surface Quality of Work Rolls Produced in a Roll Shop
4. Statistically Selecting a Rolling Oil Vendor
5. An Analysis of End-of-Line Elongation Values for Aerospace Applications
6. Conducting Appropriate Taste Analyses as Associated with Coolant Additives
7. Making a Purchasing Decision for a New Laboratory Test Device Based Upon an Appropriate Statistical Analysis (Class I Destructive Test)
8. Comparative Analysis of Saw Blade Vendors Based Upon Time to Failure (Life Analysis)
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## Advanced Statistical Process Control and Capability

### Purpose

This advanced course includes instruction from a comprehensive, applied training manual. The examples used throughout the seminar are actual examples using data gathered by personnel involved in developing and implementing process control systems and conducting capability analyses. Unique aspects of this course include short-term and process capability analysis for non-normal distributions, employing the X and Moving R chart for the control of non-normal processes, and computer applications for specialized functions.

4 days

### Number of Participants

30 participants maximum

### Prerequisites

Introduction to Statistical Process Control and Capability

### Primary Resource Materials

Advanced Statistical Process Control and Capability manual

### Content Outline

• Special Purpose Control Charts
• The Median and Range Chart
• 2. Special Purpose Control Charts
• The X and MR Chart for Applications Based Upon the Normal Distribution
• Comparison of Mean (X) and Individuals (X) Control Charts
• Testing for Normality
• The X and MR Chart for Applications Based Upon Non-Normal Distributions
• Standardized-Values Charts for Attribute Control
• Tool Wear and Trend Analysis Using the X and R Control Chart
• Statistical Analysis of Control Conditions
• Statistical Analysis of Runs
• Statistical Analysis of Trends
• Procedures for Conducting Potential, Short-Term, and Long-Term Capability Analyses
• Forms of Capability Studies
• Procedures for the Conduct of a Process Potential Study
• Process Potential Analyses
• Probability Plotting Methods
• Conducting Process Potential Studies Utilizing Computer Analyses
• Long-Term Analytical Methods and Procedures
• Normal Model Applications
• Non-Normal Model Applications
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## Introduction to Statistical Process Control for Administrative and Services Personnel

### Purpose

This course provides those personnel working in administrative and service functions with the information necessary to understand and apply statistical quality control tools to their process(es) using actual data. The course also emphasizes the importance of the quality cost/loss function analyses that relate to all administrative functions, particularly in the area of accounting. Personnel completing the course learn that their processes are quite variable and that they do have supplier/customer relationships that require continuous improvement.

4 days

No limit

None

### Primary Resource Materials

An Introduction to Statistical Process Control for Administrative and Services Personnel manual

### Content Outline

• Quality Costs and the Need for Continuous Improvement
• The Quality Cost Concept
• Quality Costs Defined
• Quality Cost Categories
• The Need for Continuous Improvement
• The Graphical Representation of Data and Basic Descriptive Statistics
• Ungrouped Frequency Distributions
• Grouped Frequency Distributions
• Frequency Polygons and Histograms
• Measures of Central Tendency
• Measures of Variability
• The Normal Distribution and z Scores
• Control Chart Theory
• Process Variation
• Control Chart Theory
• Statistical Control Conditions
• Process Control and Capability for Variables Data
• Introduction
• Developing and Interpreting X-bar and R Charts
• Introduction to Process Capability
• Process Capability Analysis from the X-bar and R Chart
• Process Control and Capability for Attribute Data
• Introduction
• Developing and Interpreting p Charts
• np, c, and u Charts
• Problem Solving and Basic Tools for the Problem-Solving Process
• Introduction
• Problem Statements
• Pareto Charts
• Flow Charts
• Brainstorming
• Fishbone Charts
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## Introduction to Statistical Process Control and Capability — Floor Applications

### Purpose

This introductory course includes instruction from a comprehensive, applied training manual. The examples used throughout the seminar are actual examples using data collected by personnel involved in developing and implementing process control systems and conducting capability analyses. This modified course is generally utilized for operator training, emphasizing a hands-on, applied approach.

4 days

### Number of Participants

30 participants maximum

None

### Primary Resource Materials

Introduction to Statistical Process Control and Capability Floor Applications manual

### Content Outline

• The Graphical Representation of Data and Basic Descriptive Statistics
• Ungrouped and Grouped Frequency Distributions
• Frequency Polygons and Histograms
• Measures of Central Tendency
• Measures of Variability
• The Normal Distribution and z Scores
• Control Chart Theory
• Process Variation
• Control Chart Theory
• Statistical Control Conditions
• Process Control & Capability for Variables Data
• Developing and Interpreting X-Bar and R Charts
• Introduction to Process Capability
• Developing and Interpreting X-Bar and s Charts
• Process Capability Analysis utilizing the X-Bar and s Chart
• Process Control and Capability for Attribute Data
• Control Charts for Defectives
• Developing and Interpreting p Charts
• Developing and Interpreting np Charts
• Control Charts for Defects
• Developing and Interpreting c Charts
• Developing and Interpreting u Charts
• How to Get Started in Statistical Process Control
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## Introduction to Statistical Process Control and Capability

### Purpose

This introductory course includes instruction from a comprehensive, applied training manual. The examples used throughout the seminar are actual examples using data collected by personnel involved in developing and implementing process control systems and conducting capability analyses. A modified course is available for operator training, which emphasizes a hands-on approach.

4 days

### Number of Participants

30 participants maximum

None

### Primary Resource Materials

An Introduction to Statistical Process Control and Capability manual
Quality with Confidence in Manufacturing
Process Control Technology workbook

### Content Outline

• The Graphical Representation of Data and Basic Descriptive Statistics
• Ungrouped and Grouped Frequency Distributions
• Frequency Polygons and Histograms
• Measures of Central Tendency
• Measures of Variability
• The Normal Distribution and z Scores
• Control Chart Theory
• Process Variation
• Control Chart Theory
• Statistical Control Conditions
• Process Control and Capability for Variables Data
• Developing and Interpreting X-Bar and R Charts
• Introduction to Process Capability
• Developing and Interpreting X-Bar and s Charts
• Process Capability Analysis utilizing the X-Bar and s Chart
• Process Control and Capability for Attribute Data
• Control Charts for Defectives
• Developing and Interpreting p Charts
• Developing and Interpreting np Charts
• Control Charts for Defects
• Developing and Interpreting c Charts
• Developing and Interpreting u Charts
• How to Get Started in Statistical Process Control
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