Compare courses
Register
ICTD International Centre for Training and Development

Practical Statistical Analysis of lab Data

This course has no confirmed dates in the future. Subscribe to be notified when it is offered.

Relevant courses

Course format
Starting after
Ending before

Disclaimer

Coursalytics is an independent platform to find, compare, and book executive courses. Coursalytics is not endorsed by, sponsored by, or otherwise affiliated with ICTD International Centre for Training and Development.

Full disclaimer.

Description

This training course is designed to help the participants master the use of statistical techniques in analyzing laboratory and make proper judgments, conclusions and recommendation. In the laboratory environment, massive data is generated as a result of the continuing measurements, testing and calibration processes.

In this course participant will discover how to derive technically and managerially meaningful facts from the information gathered through their measurements and data collection programs. It presents quantitative and qualitative tools they can apply to analyze data obtained from measurements, daily reports, surveys and external data sources.

Participants will have the opportunity to apply the principles learned to actual problems through the use of illustrative case studies under the guidance of the instructor.

Course Objectives

Upon successful completion of this course, the delegates will be able to:

  • Define data categories that are relevant to lab functions
  • Detect and eliminate outliers to assure data adequacy and integrity
  • Summarize data for effective reporting and communication
  • Carry out significance tests for different purposes
  • Define what statistical test to use
  • Explain the impact of sample size on statistical significance and power
  • Apply statistical process control charts to measurement processes
  • Analyze and interpret data for making fact-based conclusions and effective decisions

Course Outline

Day 1

Laboratory Data

  • Laboratory Functions, Systems and Culture
  • Laboratory’s Role in Enterprise Performance
  • Laboratory Quality Measures, Types of Data in Laboratory Environment, Managing Laboratory Information
  • Assuring Quality in Laboratory Data
  • Fundamentals, Dimensions and Determinants of Quality
  • Data Types and Analysis Requirements in Laboratory Quality Management Standards

Day 2

Statistical and Descriptive Categories of Data

  • Categories of Data
  • Data Collection Techniques and Tools
  • Data Adequacy, Quality, Stability, and Integrity
  • Statistical Terminology, Populations and Samples
  • Descriptive and inferential Statistics
  • Descriptive Statistics Central Tendency and Variation
  • Concept and Measurement of Dispersion
  • Statistical Histograms and Charts for Effective Graphical Data Display
  • Estimation of Parameters, Proportions and Statistics

Day 3

Statistical, Distributions, and Design on Laboratory

  • Statistical Distribution
  • Normal Distribution and Testing Normality Assumptions
  • Associative Studies, Correlation and Analysis and Regression, Setting and Testing of Hypothesis
  • Confidence Intervals
  • Design of Experiments and the Analysis of Variance (ANOVA)

Day 4

Measurement, Accuracy, Process, and Variable on Laboratory

  • Measurement System Analysis
  • Accuracy, Precision, Stability and Linearity
  • Gage Repeatability and Reproducibility
  • Concept of Stability and Capability
  • Process and Capability Indicators- Short Term and Long Term, Process Capability Indicators – Potential and Actual, Interpreting Process Capability Value
  • Statistical Process Control (SPC)
  • Variable and Attribute Control Charts

Day 5

Validation, Inter-Laboratory, Test Data, and Scoring and Analysis

  • Validation Methods, Validation Using Statistical Process Control, Measurement Uncertainty Calculations
  • Inter-Laboratory Studies and Proficiency Testing
  • Scoring and Analysis of Proficiency Test Data
  • Understanding Z-Scores in Proficiency Testing and Making the Proper Decisions, Data for Measuring Performance in Laboratory work and Establishing a Lab Scorecard

Course Methodology

A variety of methodologies will be used during the course that includes:

  • (30%) Based on Case Studies
  • (30%) Techniques
  • (30%) Role Play
  • (10%) Concepts
  • Pre-test and Post-test
  • Variety of Learning Methods
  • Lectures
  • Case Studies and Self Questionaires
  • Group Work
  • Discussion
  • Presentation

Who should attend

This course is intended for all Laboratory Technicians, Scientists, Laboratory Managers, R&D Managers, Research Supervisors, and others who need to learn and understand statistical methods of data analysis.

Files

Detailed Description
Detailed Description
Show more

Course reviews

Reviews for this course are not publicly available