CHEM: Errors in Chemical Analysis Flashcards
(TRUE OR FALSE)
Data of unknown quality are useless!
true
(true or false)
All laboratory measurements contain
experimental error.
true
true or false
It is necessary to determine the magnitude of the accuracy and reliability in your measurements.
true
true or false
No measurement is perfectly accurate or exact. Many instrumental, physical and human limitations cause measurements to deviate from the “true” values of the quantities being measured. These deviations are called “experimental uncertainties,” but more commonly the shorter word “error” is used.
true
two or more determinations on the same sample
Example: One student measures Fe (III) concentrations six times.
Replicates
average or arithmetic mean
Mean
the middle value of replicate data
median
(true or false)
If an odd number of replicates, the middle value of replicate data
true
(true or false)
If an even number of replicates, the middle two values are averaged to obtain the median
true
describes the reproducibility of measurements.
Precision
How close are results which have been obtained in exactly the same way?
Precision
derived from the deviation from the Mean
reproducibility
of an element of a data set is the absolute difference between that element and a given point. Typically the point from which the deviation is measured is the value of either the median or the mean of the data set
absolute deviation (D)
is the average of the absolute deviations and is a summary statistic of statistical dispersion or variability.
Average absolute deviation or Average deviation or mean absolute deviation
Average absolute deviation or Average deviation or mean absolute deviation
Standard Deviation
is a measure of the dispersion of a collection of number
Standard Deviation
measures the spread of the data about the mean value. It is useful in comparing sets of data which may have the same mean but a different range
Standard Deviation
is a measure of statistical dispersion
Variance
is the average squared deviations about the mean. Thus, variance is the square of the standard deviation.
variance
is a normalized measure of dispersion of a probability distribution. It is defined as the ratio of the standard deviation to the mean
Coefficient of Variation (CV)
the closeness of the measurement to the true or accepted value
Accuracy
called as the error:
absolute or relative error of a result to its true value.
closeness
Occasional error that obviously differs significantly from the rest of the results
Outlier
Described by the standard deviation, the variance and the
coefficient of variation (all are function of the deviation from the mean).
•Precision
Described by the absolute and relative error.
Accuracy
the difference between the experimental value and the true value. Has a sign and experimental units
Absolute Error (E)
the absolute error corrected for the size of the measurement or expressed as the fraction, %, or parts-per-thousand (ppt) of the true value. Er has a sign, but no units.
Relative Error (Er)
true or false
Systematic or determinate errors affect accuracy
true
( true or false)
Random or indeterminate errors affect precision!
true
(true or false)
Gross errors or blunders lead to outlier’s and require statistical techniques to be rejected.
true
failure to calibrate, degradation of parts in the instrument, power fluctuations, etc
Instrument errors
errors due to no ideal physical or chemical behavior - completeness and speed of reaction, interfering side reactions, sampling problems
Method errors
occur where measurements require judgment, result from prejudice, color acuity problems
Personal errors
Potential Instrument Errors
Variation in temperature
•Contamination of the equipment
•Power fluctuations
•Component failure
All of these can be corrected by calibration or proper instrumentation maintenance.
method errors
Slow or incomplete reactions
•Unstable species
•Nonspecific reagents
•Side reactions
These can be corrected with proper method development
Personal Errors
Misreading of data
•Improper calibration
•Poor technique/sample preparation
•Personal bias
•Improper calculation of results
These are blunders that can be minimized or eliminated with proper training and experience
Es is of the same magnitude, regardless of the size of the measurement.
•This error can be minimized when larger samples are used. In other words, the relative error decreases with increasing amount of analyte.
Constant errors
Es increases or decreases with increasing or decreasing sample size, respectively. In other words, the relative error remains constant.
Proportional errors
true or false
- Analysis of standard samples
•2. Independent Analysis: Analysis using a “Reference Method” or “Reference Lab”
•3. Blank determinations
•4. Variation in sample size: detects constant error only
true
true or false
caused by uncontrollable variables which normally cannot be defined
•The accumulated effect causes replicate measurements to fluctuate randomly around the mean.
• Random errors give rise to a normal or Gaussian curve.
• Results can be evaluated using statistics
• Usually statistical analysis assumes a normal distribution
true
named after Carl Friedrich Gauss
•characteristic symmetric “bell shape curve” that quickly falls off towards plus/minus infinity
Normal or Gaussian Curve
(true or false)
gross errors cause an experimental value to be discarded.
• Lead to outlier’s and require statistical techniques to be rejected.
true
Examples of _________ are an obviously “overrun end point“ (titration), instrument breakdown, loss of a crucial sample, and
discovery that a “pure” reagent was actually contaminated.
gross error
true or false
We do NOT use data obtained when gross error has occurred during collection.
true
