Tabtrainer Minitab: One Sample Poisson Rate
Published 4/2025
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
What you’ll learn
Total Occurrences and defect rates of poisson distributed data
Graphical derivation of the Poisson distribution
Interpreting the probability density of the Poisson distribution
Normal approximation in the context with the Poisson distribution
Determine total occurrences in Poisson distribution
Hypothesis definitions for poisson distributed data
Working with the sum function in the context of the Poisson distribution
Requirements
No Specific Prior Knowledge Needed: all topics are explained in a practical step-by-step manner.
Description
Overview
Section 1: Einführung
Lecture 1 Introduction and Business Case
Lecture 3 Choosing the Right Distribution: Why Poisson Fits Our Scenario
Lecture 4 From Sample to Population: Understanding the Poisson Approach
Lecture 5 Conducting a One-Sample Poisson Hypothesis Test to Assess Process Quality
Lecture 6 From Sample Insights to Population Estimates: Understanding λ or μ
Lecture 7 Making Decisions with Confidence: Interpreting the Poisson Hypothesis Test Resul
Lecture 8 Summary of the Most Important Findings
Quality Assurance Professionals: Those responsible for monitoring production processes and ensuring product quality will gain practical tools for defect analysis.,Production Managers: Managers overseeing manufacturing operations will benefit from learning how to identify and address quality issues effectively.,Six Sigma Practitioners: Professionals looking to enhance their expertise in statistical tools for process optimization and decision-making.,Engineers and Analysts: Individuals in manufacturing or technical roles seeking to apply statistical methods to real-world challenges in production.,Business Decision-Makers: Executives and leaders aiming to balance quality, cost, and efficiency in production through data-driven insights and strategies.
