chapter 1 Introduction (Engineering Modelling and Analysis) -- chapter 2 Introduction (Accuracy, Speed and Algorithms) -- chapter 3 Roots of Equations (Introduction) -- chapter 4 Roots of Equations (Bracket Methods) -- chapter 5 Roots of Equations (Open Methods) -- chapter 6 Numerical Integration (Trapezoidal Rule) -- chapter 7 Numerical Integration (Simpson’s Rule) -- chapter 8 Numerical Interpolation (Newton’s Method) -- chapter 9 Numerical Interpolation (Cubic Splines and Other Methods) -- chapter 10 Systems of Linear Equations (Introduction) -- chapter 11 Systems of Equations (Gauss-Seidel Method) -- chapter 12 9 LU decomposition -- chapter 13 Ordinary Differential Equations (Euler’s Method) -- chapter 14 7 Introduction -- chapter 15 Finite Difference Modelling (Introduction) -- chapter 16 Finite Difference Modelling (Laplace’s Hot Plate) -- chapter 17 1 Introduction -- chapter 18 9 Introduction -- chapter 19 9 Introduction -- chapter 20 Finite Difference Modelling (Alternate Schemes) -- chapter 21 Probability and Statistics (Descriptive Statistics) -- chapter 22 Probability and Statistics (Population and Sample) -- chapter 23 5 Introduction -- chapter 24 Probability and Statistics (Correlation and Regression) -- chapter 25 Probability and Statistics (Multiple Regression) -- chapter 26 Probability and Statistics (Non-Linear Regression) -- chapter 27 7 Discrete variables -- chapter 28 Probability Distributions (Bernoulli, Binomial, Geometric) -- chapter 29 Probability Distributions (Poisson, Exponential, Gamma) -- chapter 30 Probability Distributions (Normal and Log-Normal) -- chapter 31 Probability Distributions (Extreme Values) -- chapter 32 Probability Distributions (Chi-Square and Rayleigh) -- chapter 33 Probability Distributions (Multivariate) -- chapter 34 Monte Carlo Method (Introduction) -- chapter 35 Monte Carlo Method (Generation of Random Numbers) -- chapter 36 Monte Carlo Method (Acceptance/Rejection) -- chapter 37 Monte Carlo Method (Metropolis Applications) -- chapter 38 Stochastic Modelling (Goodness of Fit and Model Calibration) -- chapter 39 Stochastic Modelling (Likelihood and Uncertainty) -- chapter 40 Stochastic Modelling (Markov Chains) -- chapter 41 Stochastic Modelling (Time Series) -- chapter 42 Optimisation (Local Optimisation) -- chapter 43 Optimisation (Global Optimisation) -- chapter 44 Linear Introduction -- chapter 45 Spectral Analysis (Introduction) -- chapter 46 Spectral Analysis (Discrete Fourier Transform) -- chapter 47 Spectral Analysis (Practical Aspects I) -- chapter 48 Spectral Analysis (Practical Aspects II).