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Chapter 5 Some Important Hypothesis Tests
Chapter 6 Analysis of Variance
Chapter 7 Control Charts
Chapter 8 Straight Line Regression and Calibration
Chapter 16 The 2x2 Contingency Table
Chapter 17 Principal Components
Chapter 18 Information Theory
Chapter 19 Fuzzy Methods
Chapter 20 Process Modelling and Sampling
Chapter 21 An Introduction To Experimental Design
Chapter 22 Twolevel Factorial Designs
Chapter 23 Fractional Factorial Designs
Chapter 9 Vectors and Matrices
Chapter 10 Multiple and Polynomial Regression
Chapter 11 Nonlinear Regression
Chapter 12 Robust Statistics
Chapter 13 Internal Method Validation
Chapter 14 Method Validation by Interlaboratory Studies
Chapter 15 Other Distributions
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Anal analysis analytical chemistry ANOVA applied assay bias box plot calculated calibration line candidate solutions carried central composite design Chapter chart Chem chemometrics column compute concentration confidence interval confidence limits considered contingency table correlation coefficient data of Table defined degrees of freedom described detection limit determine effect equal equation estimate example experimental design experiments factorial design factors function fuzzy fuzzy set genetic algorithms given homoscedasticity hypothesis test instance interaction IUPAC laboratory least squares linear matrix mean measurement median mixture multivariate negative non-linear normal distribution null hypothesis observations obtained optimization outcome outliers parameters plot population positive possible precision prediction probability problem procedure random regression line replicate represents residual response robust regression sample Section selection shown in Fig significant simplex situation slope spline standard deviation statistical string sum of squares systematic error t-test term variables variance vector yields zero
Page 41 - ... procedure a very large number of times. The smaller the systematic part of the experimental errors which affect the results, the more accurate is the procedure.
Page 41 - ... precision: The closeness of agreement between the results obtained by applying the experimental procedure several times under prescribed conditions. The smaller the random part of the experimental errors which affect the results, the more precise is the procedure.
Page 16 - A research physicist at the National Bureau of Standards (now the National Institute of Standards and Technology) from 1951-1969, he was its director from 1 969- 1 972.
Page 44 - ... obtained by multiplying the combined standard uncertainty by a coverage factor k...
Page 40 - This process is called randomization. 2.82 true value : The value which characterizes a quantity perfectly defined in the conditions which exist at the moment when that quantity is observed (or the subject of a determination). lt is an ideal value which could be arrived at only if all causes of measurement error were eliminated and the population was infinite.