Worked solutions to all 164 end-of-chapter exercises and 57 worksheet practicals (353 numbered worksheet questions) in The R Software: Fundamentals of Programming and Statistical Analysis (Springer, 2013) — data structures, import and export, data manipulation, plots, programming, sessions, matrix algebra and optimisation, descriptive statistics, simulation, confidence intervals and tests, linear regression and ANOVA — with executed R code and committed output throughout.
Textbook Solutions
Worked solutions to all 624 exercises in Casella & Berger's Statistical Inference (2nd edition) — probability theory, transformations and expectations, common families of distributions, multiple random variables, properties of a random sample, principles of data reduction, point estimation, hypothesis testing, interval estimation, asymptotic evaluations, and the analysis of variance and regression.
Worked solutions to all 215 exercises in Bayesian Data Analysis (3rd edition) by Gelman, Carlin, Stern, Dunson, Vehtari and Rubin — probability and inference, single- and multi-parameter models, hierarchical models, model checking and comparison, MCMC and Hamiltonian Monte Carlo, variational inference, regression and generalized linear models, and nonparametric Bayesian models.
Worked solutions to all 467 exercises in Stephen Abbott's Understanding Analysis (2nd edition) — the real numbers and completeness, sequences and series, the topology of R, functional limits and continuity, the derivative, sequences and series of functions, the Riemann integral, and the additional topics chapter from metric spaces to Fourier series.
Worked solutions to all 203 exercises in Jeffrey S. Rosenthal's A First Look at Rigorous Probability Theory (2nd edition) — probability triples and extension theorems, random variables, expected values, inequalities and convergence, distributions, gambling games, discrete Markov chains, weak convergence, characteristic functions, decomposition of laws, conditional expectation, and martingales.
Worked solutions to all 342 exercises in Adnan Darwiche's Modeling and Reasoning with Bayesian Networks — propositional logic, probability calculus, building Bayesian networks, exact inference by variable elimination, factor elimination and conditioning, jointrees and graph decomposition, MPE and MAP, complexity, compilation, belief propagation, sampling, sensitivity analysis, and parameter/structure learning.
Worked solutions to all 1062 problems in Royden & Fitzpatrick's Real Analysis (4th edition) — Lebesgue measure and integration for functions of a single real variable, differentiation and integration, the Lp spaces, metric and topological spaces, Banach and Hilbert spaces, and general measure and integration theory.
Worked solutions to all 237 exercises in Terence Tao's An Introduction to Measure Theory (AMS GSM 126) — elementary and Lebesgue measure, the Lebesgue integral, abstract measure spaces, modes of convergence, differentiation theorems, outer measures and product measures, probability spaces, and the Kolmogorov extension theorem.
Worked solutions to all 100 homework problems in Mung Chiang's Networked Life: 20 Questions and Answers — CDMA power control, Google ad auctions and PageRank, Netflix recommendations, rating aggregation, Wikipedia, viral products, influence in social networks, six degrees, Internet topology, usage pricing, TCP congestion control, P2P, cloud, IPTV, WiFi, 4G, and fairness — with runnable jupyter-python experiments.