COURSE 2 OF THE EDA & SPC PROGRAM

Statistical Metrics & Normal Distribution

Providing industry professionals with self-paced, flexible, and practical training in data analysis.
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DETAILS

2 Lessons

Focused learning

Advanced Level

Ideal for professionals

60 days to complete

Complete at your pace

Flexible Schedule

Study anytime
About
What you get
Program
Certification
Meet the Trainer

This is part of the EDA & SPC Program

Ideal for those seeking a complete, guided learning experience, this option combines three courses instead of a standalone session.
  • Language: English
  • 3 Courses, 9 lessons
  • 1:1 mentoring session with the trainer.
  • Case studies across multiple industrial sectors, including Automotive, Moulds & Plastics, Pharmaceutical, Food, Logistics, Chemical, and more.
  • Excel tools with examples of how to plot histogram, normality plot, scatterplot, box plot and others on excel, how to get the statistic metrics, how to implement SPC with the control charts and capability studies, among many others.  
Earn certificates for both the full learning program and each individual course by completing a final assessment. Certificates are issued once all questions are answered correctly. Along the way, each lesson includes a short knowledge check with unlimited attempts to help you practice what you’ve learned.
SIA certificates are proof of your expertise:
  • Demonstrates mastery of practical, real-world engineering skills.
  • Help you stand out to employers, clients, and project teams.
  • Can be shared on LinkedIn, included in your CV, or used for professional development credits.
  • Validate both technical competence and continuous learning.
Training accredited by DGERT.
Created by

Cristina Barros

Cristina Barros will be available to support you throughout the course, answering questions via the course chat and offering optional 1:1 sessions. She brings more than 26 years of experience in industrial optimization, quality engineering, and statistical analysis.
Strengthen your statistical foundation by focusing on two essential areas: fundamental statistical metrics for Exploratory Data Analysis (EDA) and the role of normal distribution in interpreting processes and supporting decision-making.

Through practical examples, you will learn how to describe data more accurately, evaluate its behaviour, and interpret results that directly contribute to effective process improvement.

Learning Objectives

  • Select and calculate the statistical metrics that describe central tendency, variability, skewness, and kurtosis.
  • Interpret these metrics in real use-case scenarios.
  • Understand the normal distribution and its role in evaluating process stability.
  • Identify deviations from normality and understand why they occur.
  • Apply normalisation techniques when appropriate.
  • Calculate probabilities related to product or process specifications.
  • Explain the relevance of the Central Limit Theorem in process analysis.

  • High-Quality Video Lessons

Step-by-step training designed to be engaging, practical, and easy to follow, so you can learn at your own pace, anytime and anywhere.

  • Downloadable Templates

Access ready-to-use materials that turn learning into action: worksheets, checklists, scripts, and frameworks to implement immediately.

  • Quizzes

Reinforce your learning with interactive challenges that help you master each concept before moving on.

  • 1:1 Sessions

Schedule a 1:1 session and receive dedicated support. Each session helps you apply what you’ve learned and move forward with total clarity.

  • Private Support & Messaging

Ask questions directly and get fast feedback so you’re never stuck or left figuring things out alone.

  • Discuss with others

Participate in our online forum, share thoughts and ideas, increase connection, get help with your studies.

Course contents

This is the course 2 of the EDA & SPC
Program

This option is ideal if you’re looking for a complete and guided learning experience, rather than a single standalone course.
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