¿James Sneyd is a Professor of Applied Mathematics at the University of Auckland, New Zealand. His research is mostly in mathematical physiology and cell biology, and he is the co-author (with Jim Keener) of the prize-winning book Mathematical Physiology. He lives beside a beach, and it is absolutely untrue that he would ever waste his time playing computer games.

Teaches mathematical and statistical methods from the point of view of practical scientific applications

Illustrates concepts using real scientific data

Request lecturer material: [...]

Part I Units and Measurement.- 1 Units.- 2 Measurement, rounding and uncertainty.- Part II Functions and Complex Numbers.- 3 Functions.- 4 Exponential and log functions.- 5 Periodic functions.- 6 Linearising functions.- 7 Complex numbers.- Part III Vectors, Matrices and Linear Systems.- 8 Vectors.- 9 Matrices.- 10 Systems of linear equations.- 11 Solving systems of linear equations using matrices.- Part IV Differentiation: Functions of One Variable.- 12 Limits.- 13 Differentiation as a limit.- 14. Differentiation in practice.- 15 Numerical differentiation.- 16 Implicit differentiation.- 17 Maxima and minima.- Part V Differentiation: Functions of Multiple Variables.- 18 Functions of multiple variables.- 19 Partial derivatives.- 20 Extreme of functions of two (or more) variables.- Part VI Integration.- 21 The area under a curve.- 22 Calculating antiderivatives and areas.- 23 Integration techniques.- 24 Numerical integration.- Part VII Differential Equations.- 25 First-order ordinary differential equations.- 26 Numerical solutions of differential equations.- Part VIII Probability.- 27 Probability foundations.- 28 Random variables.- 29 Binomial distribution.- 30 Conditional probability.- 31 Total probability rule.- Part IX Statistical inference.- 32 Hypothesis test.- 33 Hypothesis testing in practice.- 34 Estimation and likelihood.- Part X Discrete Probability Distributions.- 35 Simulation and visualisation.- 36 Mean.- 37 Variance.- 38 Discrete probability models.- Part XI Continuous Probability Distributions.- 39 Continuous random variables.- 40 Common continuous probability models.- 41 Normal distribution and inference.- Part XII Linear Regression.- 42 Fitting linear functions: theory and practice.- 43 Quantifying relationships.- References.- Index.