Kit Pemodelan Statistika
Kemungkinan maksimum dan inferensi Bayes, model linear, logistik, data cacah dan campuran, ARIMA, pemeriksaan asumsi, transformasi, resampling dan laporan model regresi.
Pembelajaran
Estimation and Maximum Likelihood Concept Card Template (Statistics)
LengkapPoint estimation and maximum likelihood: bias, variance, MSE, method of moments, analytic and numerical MLE (optim, scipy.optimize), SEs from the Hessian, likelihood ratio test, AIC
Fisher (1922, 1925); Pearson (1894); Wilks (1938); Akaike (1974); NIST/SEMATECH e-HandbookBayesian Inference Concept Card Template (Statistics, R and Python)
LengkapPrior, likelihood and posterior: beta-binomial and normal-normal updates, credible vs confidence intervals, posterior predictive, prior sensitivity, Bayes factor cautions, grid approximation in base R and numpy
Bayes (1763); Jeffreys (1961); Kass and Raftery (1995); Lindley (1957); Gelman et al. Bayesian Data Analysis (name)
Metode dan pola
Linear Regression Method Card Template (Statistics, R and Python)
LengkapSimple and multiple OLS regression: least squares, coefficient tests and CIs, R² and F test, dummies, interactions, diagnostics, HC3 robust SEs, prediction vs confidence intervals, with R and Python
Least squares (Legendre 1805); Cook (1977); White (1980); MacKinnon and White (1985) HC3; NIST/SEMATECH e-Handbook ch. 4; APA JARS-Quant (name)Logistic Regression Method Card Template (Statistics, R and Python)
LengkapBinary logistic regression: logit link, odds ratios, Wald vs likelihood-ratio tests, profile vs Wald CIs, predicted probabilities and marginal effects, classification metrics, calibration, separation and EPV, with R and Python
Cox (1958); Nelder and Wedderburn (1972); Albert and Anderson (1984); Firth (1993); Hanley and McNeil (1982); Peduzzi et al. (1996); APA JARS-Quant (name)Count Regression Method Card Template (Statistics, Poisson and NB, R and Python)
LengkapPoisson and negative binomial regression for counts: rate ratios, offsets for exposure, overdispersion check, quasi-Poisson, theta vs alpha, zero-inflation note, with R and Python
Nelder and Wedderburn (1972); Lawless (1987); Lambert (1992); Cameron and Trivedi (2013); Venables and Ripley (2002) MASS; NIST/SEMATECH e-Handbook (public domain)Linear Mixed Models Method Card Template (Statistics, R and Python)
LengkapClustered and longitudinal data: random intercepts and slopes, ICC, REML vs ML, lme4 and statsmodels MixedLM side by side, df methods, singular fits, reporting
Laird and Ware (1982); Patterson and Thompson (1971); Satterthwaite (1946); Kenward and Roger (1997); Bates et al. (2015); NIST/SEMATECH e-Handbook; APA JARS-Quant (name)Time Series and ARIMA Method Card Template (Statistics, R and Python)
LengkapDecomposition, ADF and KPSS, ACF and PACF, seasonal ARIMA identification, Ljung-Box checks, forecasts with intervals and hold-out accuracy, in R and Python
Box and Jenkins (1970); Dickey and Fuller (1979); Kwiatkowski et al. (1992); Ljung and Box (1978); NIST/SEMATECH e-Handbook 6.4; R forecast and statsmodels documentation
Verifikasi
Assumption Checklist Template (Statistics, Diagnostics, R and Python)
LengkapChecking assumptions per method family (t/ANOVA, regression, GLMs, chi-square, correlation, repeated measures and mixed models): diagnostics, R and Python code, judgement rules and remedies
NIST/SEMATECH e-Handbook of Statistical Methods; Cook (1977); Box and Cox (1964); Levene (1960); Brown and Forsythe (1974); Mauchly (1940); Greenhouse and Geisser (1959); Nelder and Wedderburn (1972); Fox and Weisberg (2019)Data Transformations Method Card Template (Statistics, R and Python)
LengkapData transformations method card – log, sqrt, Box-Cox, Yeo-Johnson, logit, z-scores, centring and ranks, percent-change interpretation and smearing back-transformation, with R and Python
Box and Cox (1964); Yeo and Johnson (2000); Duan (1983); Warton and Hui (2011); NIST/SEMATECH e-Handbook (Box-Cox)Bootstrap and Permutation Methods Card Template (Statistics, R and Python)
LengkapBootstrap percentile, basic and BCa intervals, exact and Monte Carlo permutation tests, simulation checks and seeds, in R and Python
Efron (1979); Efron and Tibshirani (1993); Davison and Hinkley (1997); NIST/SEMATECH e-Handbook; R boot and SciPy documentation