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1 - Measurement and Data Processing

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Summary

This chapter's contents refer to the material covered in Topics 11.1 and 11.2 of the IB Chemistry Specification.

CORE

SPREAD 1: Uncertainties and errors in measurement and results

Qualitative data includes all non-numerical information obtained from observations not from measurement.

Quantitative data are obtained from measurements, and are always associated with random errors/uncertainties, determined by the apparatus, and by human limitations such as reaction times.

Propagation of random errors in data processing shows the impact of the uncertainties on the final result.

Introduction

All lab work in any science subject isn't perfect. Mistakes will be made. Some will be human error; some will be related to the equipment used. No experimental result has true validity unless these errors are acknowledged and worked into any result. Remember, an error is something that prevents you from getting the true, correct result.

Before we look at the errors let's clarify a few terms related to lab work:

Qualitative data: This is all information obtained from observations not from measurement. For example, a color change or the formation of a precipitate is a qualitative observation. There can be no mathematical content to such observations.

Quantitative data: This is where the numbers come in. This data is obtained from measurements and often requires mathematical processing.

In experiments we typically measure a variable. The independent variable is affected when another variable is changed (the dependent variable). For example, in an experiment to measure how temperature affects the speed of a reaction, the independent variable is the temperature and the dependent variable would be the measured time.

Although errors can be made in recording qualitative data, the majority of errors are associated with quantitative data.

What sort of errors are there?

Essentially three types of error exist:

Systematic error: These are errors that are due to the procedure or equipment you have used. For example, an experiment to measure the quantity of gas produced (see Chapter 7) will have to overcome the gap between mixing the reagents and the gas hitting a gas syringe. Some gas will be lost. As this would be a fault of the procedure the error should be the same each time.

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Publisher: Anthem Press
Print publication year: 2019

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