Learning objectives
Students will be able to deal with different challenges related to planning of experiments, quantitative analysis, quality control and comparison of data set
Prerequisites
Knowledge of basic principles of analytical chemistry
Course unit content
The course will provide student with knowledge of theoretical principles and applications to food analysis of chemometric techniques as distribution, hypothesis testing,ANOVA, regression, experimental design and quality control
Full programme
Definition of population and sample. Population parameters and their estimators. Normal distribution. Standardized normal distribution. Hypothesis testing. Student's distribution. Student's test: comparison of two means.Comparison of two variances. Normality tests. Outliers (Grubb's test). Analysis of variance .
Experimental design. Quality control. Multivariate statistical analysis: principal component analysis, linear discriminant analysis.
Linear regression. Residual analysis. Analysis of variance.Methods of quantitative analysis: external standard, internal standard, standard addition.
Trueness
Systematic errors. Matrix effect. Certified reference materials.
Bibliography
- J.N. Miller, J.C. Miller “Statistics and chemometrics for analytical chemistry” Pearson Prentice Hall
- D.L. Massart et al. “Handbook of chemometrics and qualimetrics” Part A Elsevier
- S.R. Chrouch, F.J. Holler “Applications of Microsoft Excel in analytical chemistry” 2 ed Belmont C.A. Brooks/Cole
Teaching methods
Frontal lessons and laboratory work with Excel
Assessment methods and criteria
Oral examination and Excel exercises
Other information
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2030 agenda goals for sustainable development
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