| Capaian Pembelajaran Mata Kuliah (CPMK) | - Memahami karakteristik (mean dan variance) dan fungsi distribusi kumulatif dari: (a) distribusi univariat; (b) distribusi multivariat, masing-masing untuk distribusi
bersama, marjinal, dan bersyarat.
- Menentukan mean, variance, peluang, dan fungsi distribusi dari: (a) distribusi univariat diskret (distribusi binomial dan Poisson) dan distribusi bivariat diskret; (b) distribusi univariat kontinu (distribusi normal, gamma, t, dan F) dan distribusi bivariat (normal); masing-masing untuk distribusi bersama, marjinal, dan bersyarat.
- Dari data nyata, memperkirakan distribusi peluang dan karakterisktiknya serta
menafsirkan hasil pengamatan yang didapat.
- Menentukan distribusi dari fungsi peubah acak dan nilai ekspektasinya
menggunakan moment generating function.
- Memahami sampling acak dan distribusinya, dan pengaruh dari ukuran sampel
terhadap distribusi dan karakteristiknya.
- Memahami dan menentukan distribusi statistik terurut.
| - Demonstrate an understanding of the characteristics (mean and variance) and cumulative distribution functions of univariate and multivariate probability distributions, including joint, marginal, and conditional distributions.
- Apply appropriate methods to determine the mean, variance, probabilities, and distribution functions of discrete and continuous univariate and bivariate distributions, including joint, marginal, and conditional distributions, with applications to Binomial, Poisson, Normal, Gamma, t, and F distributions.
- Analyze real-world data to estimate probability distributions and their characteristics, and interpret the resulting statistical findings.
- Apply moment generating functions (MGFs) to derive the distributions of functions of random variables and to determine their expected values.
- Demonstrate an understanding of random sampling, sampling distributions, and the impact of sample size on the properties and characteristics of these distributions.
- Understand the concept of order statistics and derive their corresponding probability distributions.
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