ANALYTICAL SELECTIVITY AND SENSITIVITY, ASSAY QUALITY CONTROL, AND STATISTICAL COMPUTATIONS Flashcards
analytical methodology
- Plan
- Sampling
- Sample preparation
- Analytical measurements
- Data analysis
plan
Qualitative, quantitative or both?; what kind of information do we have?; which technique is suitable?, etc.
sampling
Sampling: Accuracy depends on proper sampling, characteristic of sample is very important, required good representative sample (from top, middle and bottom and mix up and take average sample).
sample preparation
Depends on analytical techniques.
analytical measurements
Which techniques are best?
data analysis
Where data acquired make sense or not
Selecting an analytical method
In order to select an analytical method correctly, it is essential to define clearly the nature of the analytical problem. In general, the following points should be considered when choosing an instrument for any measurement.
- Accuracy and precision required
- Available sample amount
- Concentration range of the analyte
- Interference in sample
- Physical and chemical properties of the sample matrix
- Number of samples to be analysed
- Speed, ease, skill and cost of analysis
figures of merit for an analytical method
- Precision
- Bias
- Sensitivity
- Detection limit
- Concentration range (Dynamic range)
- Selectivity
Precision
How close the same measurements made on the same material are to one another. The degree of mutual agreement amongst data that have been obtained in the same manner. Precision provides a measure of the random or indeterminate error of an analysis.
accuracy
How close the measurement approaches the real value.
Bias
Bias provides a measure of the systematic, or determinate error of an analytical method.
bias: x’ = x + δ +
where is x’ is the population mean, δ is the bias (perhaps caused by an interfering component), is a random component (experimental error), and x is the true value.
equations for analytical methods
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Distribution and probability: normal distribution
If we know something about the distribution of events in a population, we know something about the probability of these events
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Formula for standard deviation
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Standard error of the mean (SEM)
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Summary of samples collectable from participants
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Diagnosis of periodontal diseases using 1H NMR linked metabolics
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Electronic absorption spectrum of sodium chlorite
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Absorbance- concentration relationships
If various different concentrations of a sample are subjected to
UV/Vis radiation the different absorbance readings obtained
can be plotted on a graph against concentration.
Absorbance- concentration relationships reading graph
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Correlation and regression
- Is there a relationship between x and y?
- What is the strength of this relationship
- Pearson’s r
- Can we describe this relationship and use it to predict y from x?
- Regression
- Fitting a line using the Least Squares solution
- Is the relationship we have described statistically significant?
- Significance tests
Correlation coefficient tells us
How well our data fit a linear relationship
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Formula for Pearson’s correlation coefficient
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Best fit line
- Aim of linear regression is to fit a straight line, , ŷ = ax + b to data that gives best prediction of y for any value of x
- This will be the line that minimises distance between data and fitted line, i.e. the residuals
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finding a
- Now we find the value of a that gives the least sum of squares
- Trying out different values of a is equivalent to changing the slope of the line, while b stays constant
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finding b
- First we find the value of b that gives the least sum of squares
- Trying different values of b is equivalent to shifting the line up and down the scatter plot
Regression fit warning – dodgy correlations
- outliers
look on. ppt - more than 1 different population or contrast
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