This is an extension of the [PDCA](The%20PDCA%20Cycle.md) or [PDSA Cycle](The%20PDSA%20Cycle.md) to the domain of statistics and data science. It originates from John W. Tukey formulating the paradigm of analytical processes based on Deming’s work as follows: Question -> design -> collect -> analyse -> answer.  A cycle consists of the following 5 steps (kind of adding “problem definition” to PDCA/PDSA/PDRL): 1. Problem: [Understand the objective](1.%20Validate%20the%20objective.md) and [defined the problem](2.%20Frame%20the%20problem.md). 2. Plan: [What to measure and how](3.%20Plan%20the%20analysis.md) 3. Data: Collection, management, and cleaning - see [Exploratory Data Analysis (EDA) checklist](Exploratory%20Data%20Analysis%20(EDA)%20checklist.md) for suggestions, 4. Analysis: Constructing graphs, looking for patterns, creating data visualizations, looking for patterns, running statistical models, and explaining surprises and oddities. 5. Conclusions: Interpretation, [presenting your solution](9.%20Present%20your%20solution.md), and [reflect on your work](10.%20Reflect%20on%20the%20results.md)  Reference/Source: https://dataschools.education/about-data-literacy/ppdac-the-data-problem-solving-cycle/