Introductory Chemometrics Course Outline
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8/28 Descriptive Statistics I: Sec 2.1-2.6
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Mean and standard deviation
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Distribution of repeated measurements
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Log-normal distribution
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Sample definition and sampling distribution of the mean
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Confidence limits of the mean for large samples
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9/3 Descriptive Statistics II: Sec 2.7-2.12
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Homework: Chap 2 Exercises 3,4,5,8,
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Homework: Problem Set
1, Data Set 1 Download
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Confidence limits of the mean for small samples
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Presentation of results and uses of confidence limits
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Confidence limits of a log-normal distribution
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Propagation of error
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9/5 Inferential Statistics I: Sec 3.1-3.6,
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Homework: Chap 3 Exercises 1,2,3,4,6,
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Comparison of experimental mean with known value
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Comparison of two experimental means
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Paired t-test
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One-sided and two-sided tests
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F-Test for the comparison of standard deviations
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Outliers
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9/10 Inferential Statistics II: Sec 3.7-3.13
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Homework: Chap 3 Exercises 5,7,9,11
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Analysis of variance (ANOVA)
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Comparison of several means
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The arithmetic of ANOVA calculations
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The chi-squared test
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Testing for the normality of distribution
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Conclusions from significance tests
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9/12 Analytical Quality I: Sec 4.1-4.7C
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Homework: Chap 4 Exercises 1,2,4,6
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Sampling
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Separation and estimation of variances using ANOVA
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Sampling strategy
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Quality control methods
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Shewhart control charts for mean values and ranges
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9/17 Analytical Quality II: Sec 4.8-4.13
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Homework: Control
Chart Problem Data Set
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Establishing process limits and capability
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Average run lengths and cumulative sum charts
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Proficiency testing schemes
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Collaborative trials
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Uncertainty
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Acceptance sampling
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9/19 Instrument Calibration I: Sec 5.1-5.6
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Homework: Chap 5 Exercises 2,3,4
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Calibration graphs in instrumental analysis
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Product-moment correlation coefficient
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Regression of y on x
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Calculation of concentration and its random error
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Internal standard methodology
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9/24 No Class
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9/26 Instrument Calibration II: Sec 5.7-5.11
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Homework: Chap 5 Exercises 5,6,7
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Limits of detection
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Method of standard additions
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Use of regressions for method comparison
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Weighted regression lines
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10/1 Instrument Calibration III: Sec 5.12-5.15
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Homework: Complete Problem
Set 3; Chap 5 Exercises 9,11
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ANOVA and regressions
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Curvilinear regression methods
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Regression outliers
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10/3 Multivariate Analysis I: Sec 8.1-8.3
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Homework: Chap 8 Exercises 2b,2c
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Multivariate Data Sets
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Principle component analysis (PCA)
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10/8 Multivariate Analysis II: Sec 8.4-8.7
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Homework: Chap 8 Exercises 1,2a,2d
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Cluster analysis
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Discriminant analysis
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K-nearest neighbor method
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Disjoint class modeling
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10/10 Multivariate Analysis III: Sec 8.8
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10/12 Multivariate Analysis IV: Sec 8.9-8.11
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Principle component regression (PCR)
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Multivariate regression
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Partial least squares (PLS) regression
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10/15 Multivariate Analysis V: Sec 8.12-8.13
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Multivariate calibration
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Artificial neural networks