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ANALYSIS - Analyze lab data by quantifying error. Learning Objectives. You should be able to. Explain how error propagates or compounds in computations involving random variables. Use a rule of thumb to estimate the error in computed results. Calculate the error in a result computed using products or quotients.
A comprehensive package of statistical tools (simple, cross-sectional, and gitudinal) required in laboratory experimentation. A solid introduction to the terminology used in many applications the interpretation of assay design and validation as well as “fit-for-purpose” procedures.
When we record data in the laboratory, our task is to provide a quantitative estimate of the uncertainties in our measurements. This task divides into two parts: first, we estimate the errors on directly measured
• Why do error analysis? • If we don’t ever know the true value, how do we estimate the error in the true value? • Error propagation in the measurement chain – How do errors combine? (How do they behave in general?) – How do we do an end-to-end uncertainty analysis? – What are ways to mitigate errors?
Quantifying Random Error – Statistical Analysis of Replicated Data When reporting the results of a measured value for Unit Operations Lab you will typically report the mean value of your measured replicates along with an estimated standard error.
Learning Goals. Understand how to measure error in a lab experiment. Study how to propagate error from an initial measurement through a calcu- lation. Understand how uncertainty is an integral part of any lab experiment. Introduction. There is no such thing as a perfect measurement.
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A Student’s Guide to Data and Error Analysis. All students taking laboratory courses within the physical sciences engineering will benefit from this book, whilst researchers will find invaluable reference. This concise, practical guide brings the reader speed on the proper handling and presentation of scientific data and its curacies.
