Presentation on theme: "University of San Francisco Chemistry 260: Analytical Chemistry"— Presentation transcript:
1 University of San Francisco Chemistry 260: Analytical Chemistry Dr. Victor LauRoom 413, Harney Hall, USF
2 What is Analytical Chemistry Using chemistry principle on analyzing something “unknown”….Qualitative Analysis: the process of identifying what is in a sampleQuantitative Analysis: the process of measuring how much of the substance is in a sample.
3 Here is the SAMPLE … DO NOTHING ON THE RECEIVED SAMPLE !!!!!!!!!! LOOK AT THE SAMPLEReport all your observations on the log book before doing any non-destructive or destructive analysis
4 Reading a Burette 1The diagram shows a portion of a burette. What is the meniscus reading in milliliters?ABCDreference:
5 Reading a Burette 2How about this is?41.0041.1041.1641.20
6 Reading a BuretteA 50 mL burette can be read to ± 0.01 ml, and the last digit is estimate by visual inspection. However, in order to be able to interpolate to the last digit, the perpendicular line of sight must be followed with meticulous care. Note in these two photographs, one in which the line of sight is slightly upward and the other in which it is downward, that an interpolation is difficult because the calibration lines don't appear to be parallel.upwarddownwardperpendicular
7 Section I: Math Toolkit I: Significant FiguresSignificant Figures is the minimum number of digits needed to write a given value in scientific notation without the loss of accuracy.To be simple, sig. figs = meaningful digits9.25 x sig. figs.9.250 x sig. figsx sig. figs
8 Significant Figures in Arithmetic Addition and SubtractionIf the numbers to be added or subtracted have equal numbers of digits, the answer goes to the same decimal place as in any of the individual numbers.e.g.
9 Significant Figures in Arithmetic Multiplication and DivisionIn multiplication and division, we are normally limited to the number of digits contained in the number with the fewest significant figures.e.g.
10 Significant Figures in Arithmetic Logarithms and Antilogarithmslog y = x, means y = 10xA logarithm is composed of a characteristic and a mantissalog 339 =characteristic mantissa# of digits in the mantissa = # of sig. fig in the original numberlog 1,237 =
11 Types of ErrorEvery measurement has some uncertainty, which is called Experimental ErrorExperimental Error can be classified as Systematic, Random; andGross Error
12 Experimental Error Systematic Error Consistent tendency of device to read higher or lower than true valuee.g. uncalibrated buretRandom Error“noise”UnpredictedHigher and lower than true valueGross ErrorDue to mistake
13 Precision and Accuracy Precision is a measure of the reproducibility or a resultAccuracy refers to how close a measured value is to the “true “ value
15 Propagation of Uncertainty When we used measured values in a calculation, we have to consider the rules for translating the uncertainty in the initial value into an uncertainty in the calculated value. A simple example of this is the subtraction for two buret readings to obtain a volume delivered
16 Addition and Subtraction e1, e2, and e3 is the uncertainty of the measurements, respectively.e4 is the total uncertainty after addition/subtraction manipulationAlthough there is only one significant figure in the uncertainty, we wrote it initially as 0.041, with the first insignificant figure subscripted.Therefore, percentage of uncertainty = 0.041/3.06 x 100% = 1.3% = 1.3%3.06 (+/- 0.04) (absolute uncertainty), or 3.06 (+/- 1%)
21 Gaussian Distribution For Gaussian curve representing an “infinity” number of data set, we have(mu) = true mean(sigma) = true standard deviationFor an ideal Gaussian distribution, about 2/3 of the measurements (68.3%) lie within one standard deviation on either side of the mean.
22 Student’s t - Confidence Intervals From a limited number of measurements, it is impossible to find the true mean, , or the true standard deviation, .What we can determine are x and s, the sample mean and the sample standard deviation.The confidence intervals is a range of values within which there is a specified probability of find the true mean
23 Student’s t - Confidence Intervals t can be obtained from “Values of Student's t table” see textbook, pp.78
24 “Q-Test” for Bad Data What to do with outlying data points? Accept? Or Reject? How to determine…..
31 Calibration CurveCalibration Curve is a graph showing how the experimentally measured property (e.g. absorbance) depends on the known concentrations of the standardsA solution containing a known quantity of analyte is called a standard solution