Preface; Contents; 1 Introduction; Abstract; 1.1 General; 1.2 Trend Definition and Analysis; 1.2.1 Conceptual and Visual Trends; 1.2.2 Mathematical Trend; 1.2.3 Statistical Trend; 1.3 Trend in Some Disciplines; 1.3.1 Atmospheric Sciences; 1.3.2 Environmental Sciences; 1.3.3 Earth Sciences; 1.3.4 Engineering; 1.3.5 Global Warming; 1.3.6 Climate Change; 1.3.7 Social Sciences; 1.3.7.1 Economy; 1.3.7.2 Business; 1.3.7.3 Health; 1.4 Pros and Cons of Trend Analysis; 1.5 Future Research Directions; 1.6 Purpose of This Book; References; 2 Uncertainty and Time Series; Abstract; 2.1 General 2.2 Random and Randomness2.3 Empirical Frequency and Distribution Function; 2.3.1 Empirical Frequency and Trend; 2.4 Theoretical Probability Distribution Function (Pdf); 2.5 Statistical Modeling; 2.5.1 Deterministic-Uncertain Model; 2.5.2 Probabilistic-Statistical Model; 2.5.3 Transitional Probability Model; 2.6 Stochastic Models; 2.6.1 Homogeneity (Consistency); 2.6.2 Stationarity; 2.6.3 Periodicity (Seasonality); 2.6.3.1 Known Period Case; 2.7 Time Series Truncation; 2.7.1 Statistical Truncations; 2.8 Data Smoothing; 2.8.1 Moving Averages; 2.8.2 Difference Smoothing; 2.9 Jump (Shift) 2.10 Correlation Coefficients2.10.1 Pearson Correlation Coefficient; 2.10.2 Kendall Correlation Coefficient; 2.10.3 Spearman Correlation Coefficient; 2.11 Persistence/Nonrandomness; 2.11.1 Short-Memory (Correlation) Components; 2.11.2 Long-Memory (Persistence) Component; 2.11.2.1 Rescaled Range and Hurst Phenomenon; References; 3 Statistical Trend Tests; Abstract; 3.1 General; 3.2 Nonparametric Tests; 3.2.1 Data Ordering (Ranks); 3.3 Statistical Tests; 3.3.1 Wald-Wolfowitz; 3.3.2 Sign Test; 3.3.3 Sign Difference Test; 3.3.4 Run Test; 3.3.5 Mann-Whitney (MW) Test 3.3.6 Kruskal-Wallis (KW) Test3.3.7 Nonparametric Correlation Coefficient; 3.3.8 Spearman's Rho Test of Trend; 3.3.9 Turning Point Test; 3.3.10 Mann-Kendall (MK) Test; 3.3.10.1 Mann-Kendall Trend Search; 3.3.10.2 Sen Slope Estimator; 3.3.10.3 Spearman's Tau; 3.3.10.4 Regression Trend; 3.3.11 Two-Sample Wilcoxon Test; 3.3.11.1 Signed-Wilcoxon Test; 3.3.11.2 Wilcoxon Signed Rank Test; 3.3.12 von Neuman Test; 3.3.13 Cumulative Departures Test; 3.3.13.1 Cumulative Deviations; 3.3.14 Bayesian Test; 3.3.15 Relative Error Test; 3.3.16 t Test; 3.3.17 Cramer Test; 3.3.18 F Test; 3.3.19 Truncation Test 3.3.20 Deviations Test3.3.21 Subtraction Test; 3.3.22 Şen Autorun Test; 3.3.23 Seasonal Kendall Test; 3.4 Unit Root Model Trend Determination; 3.4.1 Integration and Dickey-Fuller (DF) Test; 3.4.2 The Kwiatkowski, Phillips, Schmidt, and Shin Test; 3.4.3 Critical Values of the KPSS Test; 3.4.4 Empirical Power of the KPSS; 3.4.5 Example: Comparison of the DF and KPSS Tests for Several Macro-Economic Time Series; 3.4.5.1 Test of Stationarity Around Mean; 3.4.5.2 Test of Stationarity Around a Linear Trend; 3.5 Parametric Tests; 3.5.1 Regression Analysis; 3.5.2 Regression Line Assumptions.

This book covers all types of literature on existing trend analysis approaches, but more than 60% of the methodologies are developed here and some of them are reflected to scientific literature and others are also innovative versions, modifications or improvements. The suggested methodologies help to design, develop, manage and deliver scientific applications and training to meet the needs of interested staff in companies, industries and universities including students. Technical content and expertise are also provided from different theoretical and especially active roles in the design, development and delivery of science in particular and economics and business in general. It is also ensured that, wherever possible and technically appropriate, priority is given to the inclusion and integration of real life data, examples and processes within the book content. The time seems right, because available books just focus on special sectors (fashion, social, business). This book reviews all the available trend approaches in the present literature on rational and logical bases.