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