Ilmu aktuaria

Ilmu pengetahuan
Bagian dari sebuah seri tentang

Umum
Sejarah Literatur Metode Filsafat
Cabang
Formal Alam Fisika Kehidupan Sosial Perilaku Kognitif Terapan
Dalam masyarakat
Komunikasi Komunitas Pendidikan Pendanaan Kebijakan Pseudosains Ilmuwan
Kerangka Kategori Indeks artikel Glosarium
l b s

Ilmu aktuaria adalah bidang ilmu yang menerapkan metode matematika dan statistika untuk mengukur risiko dalam asuransi, produk-produk keuangan, serta industri dan profesi lain. Secara umum, ilmu aktuaria menerapkan matematika untuk memodelkan hal-hal yang tidak pasti. Profesi yang bergerak di bidang ini adalah aktuaris. Di banyak negara, para aktuaris harus melewati ujian profesi untuk memastikan keahliannya. Ilmu aktuaris menghubungkan berbagai ilmu lainnya, termasuk matematika, teori peluang, statistika, ilmu keuangan, ekonomi, dan ilmu komputer. Awalnya ilmu ini menggunakan model-model deterministik dengan alat bantu berupa tabel-tabel dan premi. Ilmu ini mengalami revolusi pada tahun ke 1980 dengan semakin meningkatnya kecepatan komputer, dan penggunaan model stokastik yang digabungkan dengan teori keuangan modern.^[1]

Referensi

↑ Frees, Edward W. (Januari 1990). "Stochastic Life Contingencies with Solvency Considerations" (PDF). Transactions of the Society of Actuaries. XLII: 91–148. Diarsipkan dari asli (PDF) tanggal 2006-01-03. Diakses tanggal 2006-06-28.{{cite journal}}: Pemeliharaan CS1: Ref menduplikasi bawaan (link) Pemeliharaan CS1: Tanggal diterjemahkan otomatis (link)

Daftar pustaka

Charles L. Trowbridge (1989). "Fundamental Concepts of Actuarial Science" (PDF). Revised Edition. Actuarial Education and Research Fund. Diarsipkan dari asli (PDF) tanggal 2006-06-29. Diakses tanggal 2006-06-28.

Pranala luar

Ilmu aktuaria di Curlie (dari DMOZ)

Statistika

Statistika Deskriptif

Continuous data

Pusat	Mean aritmatik geometric harmonic Median Mode
Dispersion	Variance Standard deviation Coefficient of variation Percentile Range Interquartile range
Shape	Central limit theorem Moments Skewness Kurtosis L-moments

Count data

Index of dispersion

Summary tables

Dependence

Graphics

Pengumpulan Data

Study design	Population Statistic Effect size Statistical power Sample size determination Missing data
Survey methodology	Sampling stratified cluster Standard error Opinion poll Questionnaire
Controlled experiments	Design control optimal Controlled trial Randomized Random assignment Replication Blocking Interaction Factorial experiment
Uncontrolled studies	Observational study Natural experiment Quasi-experiment

Statistika inferensia

Statistical theory

Frequentist inference

Point estimation	Estimating equations Maximum likelihood Method of moments M-estimator Minimum distance Unbiased estimators Mean-unbiased minimum-variance Rao–Blackwellization Lehmann–Scheffé theorem Median unbiased Plug-in
Interval estimation	Confidence interval Pivot Likelihood interval Prediction interval Tolerance interval Resampling Bootstrap Jackknife
Testing hypotheses	1- & 2-tails Power Uniformly most powerful test Permutation test Randomization test Multiple comparisons
Parametric tests	Likelihood-ratio Wald Score

Specific tests

Z-test (normal) Student's t-test F-test
Goodness of fit	Chi-squared G-test Kolmogorov–Smirnov Anderson–Darling Lilliefors Jarque–Bera Normality (Shapiro–Wilk) Likelihood-ratio test Model selection Cross validation AIC BIC
Rank statistics	Sign Sample median Signed rank (Wilcoxon) Hodges–Lehmann estimator Rank sum (Mann–Whitney) Nonparametric anova 1-way (Kruskal–Wallis) 2-way (Friedman) Ordered alternative (Jonckheere–Terpstra)

Bayesian inference

Correlation	Pearson product-moment Partial correlation Confounding variable Coefficient of determination
Regression analysis	Errors and residuals Regression model validation Mixed effects models Simultaneous equations models Multivariate adaptive regression splines (MARS)
Linear regression	Simple linear regression Ordinary least squares General linear model Bayesian regression
Non-standard predictors	Nonlinear regression Nonparametric Semiparametric Isotonic Robust Heteroscedasticity Homoscedasticity
Generalized linear model	Exponential families Logistic (Bernoulli) / Binomial / Poisson regressions
Partition of variance	Analysis of variance (ANOVA, anova) Analysis of covariance Multivariate ANOVA Degrees of freedom

Kategorik / Multivariat / Deret waktu / Analisis ketahanan

Categorical

Multivariate

Time-series

General	Decomposition Trend Stationarity Seasonal adjustment Exponential smoothing Cointegration Structural break Granger causality
Specific tests	Dickey–Fuller Johansen Q-statistic (Ljung–Box) Durbin–Watson Breusch–Godfrey
Time domain	Autocorrelation (ACF) partial (PACF) Cross-correlation (XCF) ARMA model ARIMA model (Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR)
Frequency domain	Spectral density estimation Fourier analysis Wavelet Whittle likelihood

Survival

Survival function	Kaplan–Meier estimator (product limit) Proportional hazards models Accelerated failure time (AFT) model First hitting time
Hazard function	Nelson–Aalen estimator
Test	Log-rank test

Aplikasi

Biostatistics	Bioinformatics Clinical trials / studies Epidemiology Medical statistics
Engineering statistics	Chemometrics Methods engineering Probabilistic design Process / quality control Reliability System identification
Social statistics	Actuarial science Census Crime statistics Demography Econometrics National accounts Official statistics Population statistics Psychometrics
Spatial statistics	Cartography Environmental statistics Geographic information system Geostatistics Kriging