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Statistical Analysis is the practice of using data to understand performance, identify patterns and support evidence-based decision-making. At Leanscape, this tag brings together articles, insights and practical guidance on how statistical analysis is applied to improve processes, reduce variation and deliver measurable performance improvement.
Effective statistical analysis is not about complex mathematics for its own sake. It focuses on using the right data and the right methods to answer meaningful business questions. Explore content covering descriptive and inferential statistics, variation analysis, hypothesis testing and data interpretation. These resources show how statistical analysis helps teams move beyond assumptions and opinions to facts and insight.
This collection also explores how Statistical Analysis supports Lean, Lean Six Sigma and data-driven improvement. Articles examine how tools such as control charts, process capability analysis, ANOVA, regression and basic data visualisation are used within improvement projects and operational environments. You’ll find insights into how statistical analysis helps identify root causes, evaluate solutions and verify that improvements are delivering real results.
For improvement practitioners, statistical analysis provides a structured way to analyse problems, test ideas and validate outcomes. For leaders and managers, it supports better performance conversations by distinguishing between normal variation and genuine issues that require action. The emphasis is on applying statistical thinking proportionately and practically, ensuring analysis informs decisions rather than creating unnecessary complexity.
Whether you are delivering improvement projects, strengthening performance management or building organisational capability, this collection shows how Statistical Analysis enables clearer understanding, better decisions and more effective, sustainable improvement by turning data into insight and action.
Key Takeaways A p value represents the probability of observing your data (or more extreme results) if the null hypothesis
Team performance follows a four-stage developmental sequence known as Forming, Storming, Norming, and Performing. In the first stage, known as
Factors to consider when developing a data collection plan – LeanScape An Introduction to Data Collection Plans A Data Collection
A scatter plot is a powerful tool when it comes to data analysis.
A probability plot is a powerful tool for data analysis
In the exploration of measurement errors within research methodology, LeanScape delves into two critical components:
Parts Per Million Parts per million (PPM) in Lean Six Sigma is a measure of how many defects exist in
Statistical Process Control (SPC) is a powerful tool for monitoring and controlling production processes. It
The P-Value in Statistics is a measure of the probability that a given result occurred
Have you ever found yourself struggling to choose between multiple options, whether it be what product to buy, which service
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Wondering whether you should get a Six Sigma Green Belt certification? This credential trains you to lead quality improvement projects
In the quest for operational excellence, organisations invest heavily in digital dashboards and analytics. Yet the simplest, most powerful method
A recent Medium feature, “On Navigating Change: How ChangeOps, Strategy, and Maturity Drive Success”, argues that most transformation efforts falter
Key Takeaways The Kano Model, created by Dr. Noriaki Kano in 1984, categorises product features based on their impact on
BNY’s CEO Robin Vince has turbocharged the bank’s transformation since 2022 by tearing down silos, unifying the corporate culture, and
Organisations today face unrelenting pressure to do more with less. Yet chasing cost cuts without a coherent framework can undermine
In a world increasingly shaped by artificial intelligence, operations leaders face a pivotal question: how do we deploy Gen AI
In an era where “faster, cheaper, better” is more than a catchphrase, generative AI (gen AI) stands out as a
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