You are working with the text-only light edition of "H.Lohninger: Teach/Me Data Analysis, Springer-Verlag, Berlin-New York-Tokyo, 1999. ISBN 3-540-14743-8". Click here for further information.

Index S...

S/N ratio	Time-Averaging
sample	Population and Sample
	Samples
sample space	Events and Sample Space
	Venn Diagram
sampling	The Data
	Representative Samples
sampling distributions	Sampling Distributions
sampling errors	Representative Samples
Sarrus' rule	Matrix Determinants - Calculation of Order 2 and 3
Savitzky-Golay coefficients	Savitzky-Golay Filter - Coefficients
Savitzky-Golay filter	Savitzky-Golay Filter
	Savitzky-Golay Filter - Mathematical Details
scalar	Vectors - Introduction
scalar product	Scalar Product
scales	Scales
scaling of data	Scaling of Data
scatter matrix	Scatter, Covariance, and Correlation Matrix
	PCA - Different Forms
scatter plot	Autocorrelation and Scatter Plots
	Scatter Plot
scedasticity	Scedasticity
scores	Factor Analysis
	PCA - Loadings and Scores
search space	Phase Space
selection of variables	PRESS
	Variable Selection - Stepwise Regression
	Variable Selection - Introduction
	Variable Selection - Principal Approach
self organizing map	Kohonen Networks
separabability of classes	Structure of Measured Data
serial correlation	Autocorrelation
sets	Calculating with Sets
signal to noise ratio	Coefficient of Variation
signal-to-noise ratio	Signal and Noise
	Time-Averaging
signals	Signals as Time Series
significance	Level of Significance
similar mineral waters	Exercise - Similar Mineral Waters
similarity	Distance and Similarity Measures
simplex algorithm	Simplex Algorithm
single linkage clustering	Minimal Spanning Tree
singular matrix	Matrix Inversion
singular value decomposition	Singular Value Decomposition
skew-symmetric matrix	Transposed Matrix
skewness	Skewness
smoothing	Savitzky-Golay Filter - Coefficients
SNR	Signal and Noise
soft model	Modeling
solid residues	Data Set - Solid Residues in Mineral Water
SOM	Kohonen Networks
Spearman's rank correlation	Spearman's Rank Correlation
spectrum	Time and Frequency
spikes	Physical Origin of Noise
square matrix	Matrix Algebra - Fundamentals
standard deviation	Chebyshev's Theorem
	Parameters
	Standard Deviation
standard normal probability density function	Normal Distribution
standardization	Scaling of Data
state space notation	Filters - Mathematical Background
stationary time series	Time Series - Trends
statistic	Population and Sample
statistical tests	Interpreting p values
	Kolmogorov-Smirnov One-Sample Test
	Test for Normality
	Outlier Tests - Basic Rules
	One-Sample t-Test - Large Samples
	One-Sample t-Test - Small Samples
	One Sample Chi-Square-Test
	Two-Sample t-Test - Large Samples
	Two-Sample t-Test - Small Sample Size
	Two-Sample F-Test
	Chi-Square Test
	Paired Experiments
	Distribution-Free Tests
	Hypothesis Testing
	Power of a Test
	Test: Correlation Coefficient
	Randomization Tests
	Rank Randomization Tests
	Statistical Tests
stem-and-leaf plots	Stem-and-Leaf Plots
stepwise regression	Variable Selection - Stepwise Regression
stochastic matrix	Stochastic and Regular Matrix
strontium concentration	Exercise - Comparing two sample means
structure of measured data	Structure of Measured Data
subsets	Complementary Sets and Subsets
subtraction	Matrix Addition and Subtraction
	Subtraction of Vectors
summation rule	Summation of Probabilities
sun block	Modeling - Example
support	Support for Registered Users
survey on ANN models	Taxonomy of ANNs
SVD	Singular Value Decomposition
symmetric matrix	Transposed Matrix

Last Update: 2004-Oct-30