Six Sigma Basic Key Terms - Part V (Tools)

Six Sigma Basic Key Terms - Part V (Tools)

Histogram: A group of vertical bar graphs that shows the distribution of one variable in a group of data. The histogram visually represents all of a set of data points on a two – axis graph, to show the distribution of all those data points and to reveal patterns, also known as a frequency distribution bar chart.
Distribution: The organization of the data on a graph. From the distribution, you begin to turn data into usable information.

Dispersion: The degree to which values for a variable differ from each other. If every value for a variable were close, the variable would have very little dispersion, also known as variability and spread.

Variance: A measure of the amount by which a value differs from the mean, calculated as the average squared deviation of each number from its mean.

Run Chart: A graph that plots performance data over time for a process, representing the data usually as a line chart. It represents and compares numeric data, indicating changes over time with a line connection data points.

Correlation: The degree to which two variables are related, measured in terms of a correlation coefficient (between 1 and -1). Correlation does not necessarily mean causation.
Scatter Plot: A graph in which individual data points are plotted in two dimensions. Also known as a scatter diagram or a cross plot.

Correlation Coefficient: A number between -1 and 1 that measures the degree to which two variables are linearly related. If the two variables have a perfect linear relationship with positive slope, the correlation coefficient is 1; if there is positive correlation, whenever one variable has a high value or a low value, so does the other. If the two variables have a perfect linear relationship with negative slope, the correlation coefficient is -1; if there is negative correlation, whenever one variable has a high value, the other has a low value. A correlation coefficient of 0 means that the variables have no linear relationship.

XY Matrix: A group of rows and columns, with one set of increments marked along the X (horizontal) axis and another set of increments marked along the Y (vertical) axis, also known as an x-y matrix.

Pareto Chart: A representation of the relative importance of process causes or defects, based on the rule of thumb originated by the Italian economy Vilfredo Pareto, that 80% of all problems result from 20% of the causes (known as the Pareto principle or the 80/20 principle)
Multivariate study: An analysis that offers a way to reduce possible causes of variation in a process to a family of related causes, by graphing the inter-relationship of multiple variables. The multivariate chart presents an analysis of process variation by differentiating three main sources: intra – piece, inter – piece, and temporal.

Failure mode effect analysis (FMEA): The manner in which a part or process can fail to meet a specification, creating a defect or non – conformance, and the impact on the customer if that failure mode is not prevented or corrected.

Design of Experiments (DOE): A way of determining and measuring the importance of two or more factors on the outcome of a process, by experimenting with many factors and variables simultaneously, also known as multivariable testing.

Common cause: An inherent natural source of variation in the output of a process, also known as a random cause.

Special Cause: A source of variation that is both unpredictable and not due to normal causes; it’s an exception, also known as an assignable cause.

Design for Six Sigma (DFSS): A systematic methodology using tools, training, and measurements to enable the design of products, services, and processes that meet customer expectations at Six Sigma quality levels. DFSS optimizes your design process to achieve Six Sigma performance and integrates Six Sigma characteristics at the outset of new product development with a disciplined set of tools.