This final section of the Pareto Primer is all about the Quantitative Methods and Tools.
Within the pillar of the body of knowledge there are 8 major topics areas that all CQE’s must be able to understand, analyze and evaluate.
- Collecting and Summarizing Data – The first step in performing trust-worthy Quantitative analysis is a firm understanding of Data.
This chapter is broken down into two parts.
The first section includes the different types of data, measurement scales, and data collection methods,
The second section is all about descriptive statistics, including the concepts on Central Tendency, Variation, the Central Limit Theorem and the graphical methods that can be used to depict relationships & distributions.
- Probability (Quantitative Concepts) – Once you’ve collected data, it’s time to analyze that data using the following concepts of Probability:
The basic terms, definitions & concepts including Probability, Experiment, Sample Space, Events, Outcomes, Unions, Intersections, Compliments, etc.
Complex probability concepts & methods such as independence, mutual exclusivity, the multiplication & addition rule of probability, and conditional probability.
- Probability Distributions – The next level of Quantitative analysis includes a knowledge of the Distribution of your data which represent the frequency of occurrence for the data.
This section includes a review of the common probability distributions which may represent your data.
- Statistical Decision Making – This section provides the tools & methods for all sorts of statistically based tests, including Hypothesis testing, Confidence Intervals & Point Estimates, ANOVA & Contingency Tables.
- Relationships between variables – In many situations, you’ll be required to understand & analyze the relationship between variables with tools such as regression, correlation, and time-series analysis charts which is all covered within this section.
- Statistical Process Control – Statistical Process Controls (SPC) is the collection of statistical techniques used to measure and analyze the variation in processes. SPC begins by recognizing that all processes contain variation, and measurement will indicate the dispersion of the data.
- Process & Performance Capability – Process and Performance Capability starts with an analysis of your process (Process Capability Study) following by the calculations of the Process & Performance Capability Indices .
- Design and Analysis of Experiments – Designed Experiments can be a powerful tool for continuous improvement, root cause analysis, product design or process development and you must understand how to design and implement them to obtain statically sound results.