Index T...

t distribution	t Distribution
T-score	T-Scores
t-test	ANOVA
	One-Sample t-Test - Large Samples
	One-Sample t-Test - Small Samples
	One-Sample t-Test
	Two-Sample t-Test
	Two-Sample t-Test - Large Samples
	Two-Sample t-Test - Small Sample Size
	Comparing means
	Paired Experiments
	Exercise - Relative Humidity of US Cities
	Exercise - Testing the Reaction Time of a Person
	Exercise - Comparing two sample means
	Welch-Test
t-test for unequal variances	Welch-Test
table of association	Contingency Table
Tanimoto coefficient	Distance and Similarity Measures
taxonomy of ANNs	Taxonomy of ANNs
taxonomy of multivariate methods	Survey on Multivariate Methods
TDNN	Time Series - Neural Network Models
temperature	Exercise - Determine time shift by autocorrelation
test	Types of Error
	Interpreting p values
	Kolmogorov-Smirnov One-Sample Test
	Test for Normality
	Outlier Tests
	Outlier Tests - Basic Rules
	Outlier Test - Dean and Dixon
	One-Sample t-Test - Large Samples
	One-Sample t-Test - Small Samples
	One Sample Chi-Square-Test
	Two-Sample t-Test
	Two-Sample t-Test - Large Samples
	Two-Sample t-Test - Small Sample Size
	Two-Sample F-Test
	Chi-Square Test
	Comparing means
	Paired Experiments
	Distribution-Free Tests
	Hypothesis Testing
	One-Sided vs. Two-Sided Tests
	Power of a Test
	Test: Correlation Coefficient
	Randomization Tests
	Rank Randomization Tests
	Wilcoxon Test for Paired Differences
	Significance of Outliers
	Uncorrelated Residuals - Durbin-Watson Test
	Runs Test
	Shapiro-Wilk Test
	Median Test
textbooks in statistics	Literature References - Textbooks
theorem of Chebyshev	Chebyshev's Theorem
thermal noise	Physical Origin of Noise
third moment	Skewness
tied observations	Spearman's Rank Correlation
	Tied Observations
time and frequency	Time and Frequency
time dependence of data	Time Dependence of Data
time series	Literature References - Time Series
	Signals as Time Series
	Time Series - Neural Network Models
	Time Series - Definition of ARIMA Models
	Time Series - Establishing ARIMA models
	Time Series - Forecasting
	Time Series - Introduction
	Time Series - Model Finding
	Time Series - Trends
	Time Dependence of Data
time shift	Exercise - Determine time shift by autocorrelation
time-averaging	Signal and Noise
	Time-Averaging
	Time-Averaging - Mathematical Details
topological descriptors	Data Set - Boiling Points and Chemical Descriptors
trace	Matrix Algebra - Fundamentals
trains	Data Set - Delayed Trains
transformation	Curvilinear Regression
	Regression after Linearisation
transformation of data space	Transformation of the Data Space
	Transformation of the Data Space - Example: mass spectrometry
transposed matrix	Transposed Matrix
	PCA of Transposed Matrices
treatment	Experimental Design
trend analysis	Exercise - Weight Loss of Coins
trends	Time Series - Trends
triangular window	Windowing Function and FFT
trimmed data	Censored Data
trimmed mean	Mean
true positive/negative	Classifier Performance
Tukey window	Windowing Function and FFT
two-sample F-test	Two-Sample F-Test
two-sample t-test	Two-Sample t-Test - Large Samples
two-sided tests	One-Sided vs. Two-Sided Tests
types of error	Types of Error
types of noise	Types of Noise