Fundamentals of Statistics contains material of various lectures and courses of H. Lohninger on statistics, data analysis and chemometrics......click here for more. ## Index P...

 p values Interpreting p values p-chart p- and c-Charts paired differences Wilcoxon Test for Paired Differences paired experiments Paired Experiments parameter Parameters parametric tests Parametric and Non-Parametric Tests pareto distribution Pareto Distribution parsimonious model Modeling partial derivative Partial Derivative partial least squares Modeling with latent variables PLS - Partial Least Squares Regression PCA Literature References - Factor Analysis, Principal Components Principal Component Analysis Application Example of PCA - Classification of Wine Data Compression by PCA PCA - Loadings and Scores PCA - Different Forms PCA - Model Order Exercise - Dependence of PC scores on scaling of data Exercise - Classification of unknown wine samples by PCA Exercise - Detection of mixtures of two different wines by PCA Relations between Loadings, Scores and Original Data PCA of Transposed Matrices PCR Principal Component Regression Exercise - Perform a PCR by successive application of PCA and MLR Modeling with latent variables Pearson Karl Pearson Significance of Outliers Pearson's contingency coefficient Contingency Coefficient Pearson's correlation coefficient Pearson's Correlation Coefficient perceptron Multi-layer Perceptron permutation Matrix Determinant Counting Rules phase angle Fourier Series phase space Phase Space physical dimension Data Set - Physical Dimension of Fishes pink noise Types of Noise platykurtic distribution Kurtosis PLS Modeling with latent variables PLS - Partial Least Squares Regression PLS Discriminant Analysis Evaluating the performance of PLS-DA pocket calculator Decimal Places and Precision Poisson distribution Poisson Distribution Relationship Between Various Distributions polynomial filter Savitzky-Golay Filter - Mathematical Details polynomial fit Exercise - Calculate a polynomial fit by means of MLR Data Set - Polynomial Fit Curve Fitting by Polynomials population Population and Sample positive predictive value Classifier Performance power Types of Error Power of a Test precision The Data Decimal Places and Precision Definitions of Quality Control Random and Systematic Errors Classifier Performance Determination Limit prediction of future values Regression - Confidence Interval MLR - Estimation of New Observations predictive ability Predictive Ability predictor Modeling PRESS PCA - Model Order Predictive Ability Validation of Models principal component regression Principal Component Regression Exercise - Perform a PCR by successive application of PCA and MLR Modeling with latent variables principal components Literature References - Factor Analysis, Principal Components Principal Component Analysis Data Compression by PCA PCA - Different Forms Principal Component Regression Exercise - Estimation of Boiling Points from Chemical Structure Exercise - Dependence of PC scores on scaling of data Exercise - Classification of unknown wine samples by PCA Exercise - Detection of mixtures of two different wines by PCA The NIPALS Algorithm Relations between Loadings, Scores and Original Data PCA of Transposed Matrices principal diagonal Matrix Algebra - Fundamentals probability Algebra of Probabilities Bayesian Rule Conditional Probability Counting Rules Events and Sample Space Independent Events Probability - Introduction Probability Theory Exercise - Probability of Observations Exercise - Probability of a train being delayed Summation of Probabilities Additivity Rule Complementary Sets and Subsets Union and Intersection probability density function Exercise - Design a data set showing a bimodal probability density function Exercise - Design a data set showing a normal probability density function probability plot Probability Plot process control Control Charts p- and c-Charts x- and R-Charts process stability Control Charts process variability Variability processing unit ANN - Single Processing Unit propagation of errors Error Propagation pruning Variable Selection - Pruning pseudo random numbers Random Number Generators pseudo-inverse matrix Moore-Penrose Pseudo-Inverse Matrix