# Test #2 – Quantitative Analysis Flashcard

 significant figures
 the minimum number of digits needed to write a given value in scientific notation without any loss of accuracy
 interpolation
 estimate all readings to the nearest tenth of the distance between scale divisions
 significant figures in arithmetic
 in a series of calculations, carry the extra digits through to the final result then round.
 significant figures in rounding
 if the digit is to be removed and is less than 5, the preceding digit stays the sameif greater than 5, the preceding digit increases by 1if equal to 5, preceding digit remains the same or increases by 1, whichever gives an even digit
 significant figures and addition and subtraction
 round according to the number with the most uncertainty, that is, the answer is limited by the least certain number
 significant figures and multiplication and division
 the answer is limited to the number of digits contained in the number with the fewest significant figures
 significant figures and logarithms and antilogarithms
 the number of digits in the mantissa of (log x) is the number of significant figures in x.
 characteristic
 the part of a logarithm to the left of the decimal point
 mantissa
 the part of a logarithm to the right of the decimal point
 significant figures in graphs
 depends on the purpose of the graph.if to display qualitative behavior of data, then sig figs are irrelevant.if to display precise values, then several sig figs
 systematic errordeterminate error
 occurs in the same direction each time (high or low), often resulting from poor technique
 how to detect systematic error
 analyze samples of known composition, ‘blank’ samples containing none of the sought analyte; use different analytical methods to measure same quantity; Round Robin experiment
 Round Robin experiment
 assign different people/labs to analyze identical samples
 random errorindeterminate error
 measurement has an equal probability of being high or low; obeys laws of statistics
 accuracy
 agreement of a particular value with the “true” value.
 precision
 degree of agreement among several elements of the same quantity
 absolute uncertainty
 expression of the margin of uncertainty associated with a measurement
 relative uncertainty
 compares the size of the absolute uncertainty with the size of its associated measurement
 percent relative uncertainty
 100 * relative uncertainty
 propagation of uncertainty from random erroraddition and subtraction
 if A=B+-C+-DUa=(Ub^2+Uc^2+Ud^2)^1/2abs uncertainty used
 propagation of uncertainty from random errormultiplication and division
 A=B*/C*/D%RUa=[(%RUb)^2+(%RUc)^2+(%RUd)^2]^1/2percent relative uncertainty used
 propagation of uncertaintymixed operations
 same manner as the calculations are performed
 real rule of significant figures
 THe first uncertain figure is the last significant figure
 propagation of uncertaintyexponents
 %RUy=a(%RUx)
 propagation of uncertaintylogarithms
 Uy=(1/ln10)*RUx
 propagation of uncertaintynatural log
 Uy=RUx
 propagation of uncertaintypower of 10
 RUy=(ln10)Ux
 propagation of uncertaintybase e
 RUy=Ux
 uncertainty in molecular masses
 Use rule for addition and subtraction, then multiply by n moles per identical atom
 Gaussian distribution
 Theoretical bell-shaped distribution of measurements when all error is random. The center of the curve is the mean, and the width is characterized by the standard deviation.
 mean
 average  [image]
 standard deviation
 measure of how closely the data are clustered to the mean. [image]
 degrees of freedom
 the number of independent measurements
 variance
 standard deviation squared
 relative standard deviation
 100 * std. dev./ mean
 significant figures in mean and standard deviation
 where uncertainty begins according to std. dev., that’s where significant figures are.
 formula for Gaussian curve
 [image]
 Z
 [image]
 confidence interval
 [image]
 Student’s t
 statistical tool used to express confidence intervals and to compare results from different experiments.
 Student’s t test
 used to compare one set of data with another to decide whether or not they are “the same”
 null hypothesis
 the two sets of data are the same
 alternate hypothesis
 the two sets of data are different
 when to use Student’s t test
 comparing a measured result with a known value, replicate measurements, individual differences
 t calc equation known value
 [image]
 t calc equation replicate measurements if std. devs. equal
 [image]
 s pooled replicate measurements
 [image]
 t calc equation replicate measurements if std. devs. inequal
 [image]
 F test
 compares standard deviations
 F calc
 [image]
 Grubbs test
 determines whether one measurement can be thrown away — whether it is an outlier or not
 G calc
 [image]
 Dropped sample? Pretty obviousBe hesitant if not certainGrubbs test is not very reliable
 Calibration curve
 a graph showing the value of some property versus concentration of analyte. When the same property of an unknown is measured, its concentration can be determined from the graph. [image]
 method of least squares
 process of fitting a mathematical function to a set of measured points by minimizing the sum of the squares of the distances from the points to the curve.
 standard solutions
 a solution whose composition is known by virtue of the way it was made from a reagent of known purity or by virtue of its reaction with a known quantity of standard reagent
 blank solution
 a solution that does not contain analyte; used to correct for interferences
 linear range
 the analyte concentration range over which response is proportional to concentration
 dynamic range
 the analyte concentration range over which there is a measurable response to analyte.
 quality assurance
 Quantitative indications that indicate whether data requirements have been met.Also refers to the broader process that includes quality control, quality assessment, and documentation of procedures and results designed to ensure adequate data quality.
 Use objective
 states the purpose for which results will be used
 specifications
 describes how good analytical results need to be and what precautions are required in an analytical method.
 false positive
 a conclusion that the concentration of analyte exceeds a certain limit when, in fact, the concentration is below the limit
 false negative
 a conclusion that the concentration of analyte is below a certain limit when, in fact, the concentration is above the liimit.
 selectivity
 being able to distinguish analyte from other species in the the sample
 sensitivity
 the capability of responding reliably and measurably to changes in analyte concentration.Slope of the calibration curve
 method blank
 a sample containing all components except analyte and is taken through all steps of the analytical process.Response is subtracted from sample’s response.
 reagent blank
 a solution prepared from all of the reagents, but no analyte; for measuring response of analytical method to impurities in reagents and other effects caused by anything but the analyte
 field blank
 a blank sample exposed to the environment at the sample collection site and transported in the same manner as other samples between the lab and the field.
 matrix
 everything in the sample other than analyteAlso, the virtual reality which the machines have set us in while they harvest our bodies for energy. Ignore that it would be incredibly inefficient.
 spike
 addition of a known compound (with known concentration) to an unknown
 spike recovery
 [image]
 calibration check
 the analysis of a solution formulated by the analyst to contain a known concentration of analyteEnsures that procedures and instruments are functioning correctly.
 performance test samples
 inserted in a series of measurements to see if a procedures gives correct results when the analyst does not know the right answer
 standard operating procedures
 a written procedure that must be rigorously follow to ensure the quality of a chemical analysis
 control chart
 a visual representation of a confidence interval for a Gaussian distribution
 assessment
 the process of collecting data to show that analytical procedures operating within specified limits and verifying that final results meet use objectives
 method validation
 the process of proving that an analytical process is acceptable for its intended purpose
 specificity
 the ability of an analytical method to distinguish the analyte from everything else that might be in the sample
 linearity
 measures how well a calibration curve follows a straight line
 square of the correlation coefficient
 measure of goodness of fit of data points to a straight line.Closer to 1 = better
 how to demonstrate accuracy
 Analyze a standard reference materialcompare results of different methodsspike a blank sample with analytestandard additions
 reproducibility of results
 precision(alternate definition)
 range
 concentration interval over which linearity, accuracy, and precision are all acceptable
 detection limit
 the smallest quantity of analyte that is “significantly different” from the blank.**
 procedure for detection limit determination
 [image]
 quantitation limit
 [image]
 reporting limit
 the concentration below which regulatory rules say that a given analyte is reported as “not detected”
 robustness
 the ability of an analytical method to be unaffected by small, deliberate changes in operating parameters
 known quantities of analyte are added to the unknown and the responses are recorded. This keeps any matrix effect constant.
 matrix effect
 a change in the analytical signal caused by anything in the sample other than the analyte