• In the analysis phase, the root causes of the problems are determined (What is wrong?)

• This phase involves examining the processes and the data to understand the causes of the problems and opportunities for improvement

• The x and y data collected in the measurement phase are analyzed to understand the relationship between the response variable y and the input variables x using the relat ionship y=f(x)

• The key deliverable from the analysis phase is validated root causes

Objective

• Understand the current process performance, and the data collected in

• the measure phase

• Understand the statistical tools to be used in the analysis phase

• Understand how the analysis tools will be used to analyze the data

• Understand the variation, sources of variation, and components of variation in the process

• Determine through analysis how the input variables influence the output variables

• Determine the key input variables that influence the output variables

• Analyze the data to determine whether they support or fail to support the hypothesis about magnitudes of certain population parameters (test the research hypotheses)

• Use the appropriate inference procedure tools (hypothesis tests) to draw appropriate conclusion about the mean, variance, standard deviation of selected variables

• Use the analysis of variance (ANOVA) techniques to analyze data taken from

• multiple populations

• Revise the process maps if necessary to make sure that the

• process maps represent the actual or desired flow of the process

• Study the process to identify the sources of errors, the root causes of the problems, bottlenecks, and non-value added activities (waste) from the process,

• Establish improvement goals