Statistics, Calibration Strategy & Data Processing

Abstract

Over the past few decades, instrumental analysis has come a long way in terms of sensitivity, efficiency, automation, and the use of sophisticated software for instrument control and data acquisition and processing. However, the full potential of such sophistication can only be realized with the user’s understanding of the fundamentals of method optimization, statistical concepts, calibration strategies and data processing, to tailor them to specific analytical needs without blindly accepting the output data provided by the instrument.

The objective of this course is to provide the necessary knowledge to strategically exploit the full potential of such capabilities and commonly available spreadsheet software. Topics to be covered include:

Analytical Statistics:

• Propagation of Errors
• Systematic and Random Errors
• Limit of Detection and Quantification

Data Analysis Using Spreadsheets:

• Template Development for Routine Calculations
• Building “Intelligence” Into Spreadsheets
• Evaluation and Visualization of Large Data Sets
• Universally Applicable Concepts using Examples from ICP-ES/MS and Chromatographic Data

Calibration:

• Linear and Nonlinear Regression
• Weighted Versus Unweighted Regression
• Dynamic Range (Use and Misuse)
• Selecting Optimal Intervals for Standards
• Preparation of Standards: Gravimetric vs Volumetric

Interferences – Causes and Remedies:

• Matrix Effects and Signal Drifts
• Signal Noise and Measurement Uncertainty
• Standard Addition & Internal Standardization
• Matrix-matched Standards

Although the demonstration data sets will be primarily selected from ICPES/MS and Chromatographic measurements, the concepts discussed will be applicable to any analytical technique, and scientific measurements in general to benefit a broader audience.

Please note that the language of instruction is English only.

For further inquiries: ndesilva@uottawa.ca