Chapter_5 - Chapter 5 Errors in Chemical Analysis Every...

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Unformatted text preview: Chapter 5 Errors in Chemical Analysis Every measurement is influenced by many uncertainties. Uncertainties can never be completely eliminated. True value for a quantity is always unknown. Probable magnitude of error in a measurement can often be evaluated. Reliability of data can be assessed by: Experiments designed to reveal presence of errors can be performed. Standard of known composition can be analyzed and results compared with known composition. Calibration of equipments. Application of statistical tests to the data. Mean: Divide the sum of the replicate measurements by the number of measurements in the set. Median: Middle result when replicate data are arranged in order of size. Precision: Reproducibility of measurement. Described by standard deviation, variance, coefficient of variance. Accuracy: Closeness of measurements to its true value. Expressed as absolute error and relative error. Differences between Accuracy and Precision Accuracy Agreement among results and true value Never be determined exactly Precision Agreement between several results Determined by replicate measurements Absolute Error (E): Difference between measured value and true value. Relative Error (Er): Absolute error divided by the true value. Types of Errors Random Errors (Indeterminate): Scattered symmetrically around a mean value - reflected by precision Systematic Errors (Determinate): Results in a replicate measurement are all high or all low affects accuracy of results Sources of Systematic Errors 1. Instrument Errors A. Measuring Devices: deliver volumes slightly different from those indicated by their graduation temperature difference from calibration temperature Distortion of container walls due to heating Error in original calibration Contamination on inner surfaces of containers Sources of Systematic Errors 1. Instrument Errors B. Electronic Instruments: Instrumental systematic error (decrease of voltage with use, increased resistance due to dirty electrical contacts Temperature changes (variation in resistors and standard potential sources) Current induced from 110-V power lines Easily detectable and removed by Sources of Systematic Errors 2. Method Errors Non-ideal chemical and physical behavior of reagents and reactions Examples: 1. 2. Small excess added during titration to reach end point Incomplete decomposition of compounds having pyridine rings in Kjeldahl determination of nitrogen (negative errors) Difficult to detect and most serious Sources of Systematic Errors 3. Personal Errors Position of a pointer between two scale divisions Color of a solution at the end point of a titration Error in volume reading Sources Prejudice Number bias Favoring small digits over large, even over odd Removed using digital readouts and guard against personal bias Types of Systematic Errors Constant Errors: Magnitude does not depend on the size of the quantity measured. More serious as the size of the quantity measured decreases. Examples: Loss of ppt during filtration in gravimetric analysis Excess reagent required to bring color change in titration Minimizing: Use large sample Types of Systematic Errors Proportional Errors: Increase or decrease in proportion to the size of the sample Caused by the presence of interfering contaminants Examples: Interference of Fe in the iodimetric determination of Cu Interference of Mo and W in the determination of each other Interference of Ca in EDTA titration of Mg Size of the error depends on the fraction of the contanimation in the sample Detection of Systematic Errors Instrument Errors Detected and corrected by periodic calibration Personal Errors Care Self-discipline Check instrumental readings Detection of Systematic Errors Method Errors 1. Analysis of Standard Samples Standard materials prepared by synthesis - Measured quantities of pure components of a material are mixed homogeneously - Sometimes difficult and time consuming Standard reference material (NIST) - Analyzed by previously validated reference methods - Analyzed by independent reliable methods - Analyzed by network of cooperating laboratories Detection of Systematic Errors Method Errors 2. Second Independent Analysis ( when standard samples not available) - Method under study compared with a second independent reliable analytical method - Independent method should differ as much as possible from the method under study (to eliminate the effect of any common factor) - Statistical test used to determine whether difference between two methods is random error or method bias Detection of Systematic Errors Method Errors 3. Blank Determinations - All steps of analysis performed without the sample - Results applied as a correction to sample measurements - Reveals the presence of interfering contaminants 4. Variation in Sample Size - Detected by varying the sample size - Effect of an error decreases as size of a measurement increases ...
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