Mata Kuliah ET2101 - 2024

Kode Mata KuliahET2101 / 3 SKS
Penyelenggara181 - Teknik Telekomunikasi / STEI
KategoriKuliah
Bahasa IndonesiaEnglish
Nama Mata KuliahProbabilitas dan StatistikProbability and Statistics
Bahan Kajian
  1. Teori Peluang
  2. Teknik statistik
  3. Konsep probabilitias
  4. Peubah acak
  5. Distirbusi propabilitas diskrit
  6. Distirbusi propabilitas kontinyu
  7. Fungsi pada peubah acak
  8. Teori estimasi
  9. Hipotesa
  1. Probability Theory
  2. Statistics
  3. Concept of Probability
  4. Random Variables
  5. Discrete Probability Distribution
  6. Continuous Probability Distribution
  7. Functions of Random Variables
  8. Estimation Theory
  9. Hypothesis Test
Capaian Pembelajaran Mata Kuliah (CPMK)
  1. Kemampuan untuk memahami hubungan ilmiah dan matematis (prinsip atau hukum) dan masukan yang diperlukan pada teori peluang
  2. Kemampuan mengidentifikasi dan merumuskan permasalahan teknik pada suatu aplikasi berdasarkan teori peluang
  3. Kemampuan menganalisis dan menyelesaikan permasalahan teknik pada suatu aplikasi berdasarkan teori peluang
  1. Ability to understand scientific and mathematical relationships (principles or laws) and the necessary input to probability theory
  2. Ability to identify and formulate technical problems in an application based on probability theory
  3. Ability to analyze and solve technical problems in an application based on probability theory
Metode PembelajaranCeramahLecture
Modalitas PembelajaranLuring Sinkron Daring Asinkron BauranSynchronous Offline Asynchronous Online Hybrid
Jenis NilaiABCDE
Metode PenilaianKuis, UTS, UASquiz, Midtest, Final Test
Catatan TambahanSilabus kuliah : Mata kuliah ini membahas fondasi probabilitas dan statistika: pemodelan ketidakpastian, peubah acak diskrit/kontinu, sebaran peluang penting, transformasi peubah acak, hingga dasar‐dasar teori pencuplikan dan pembangkitan sampel acak. Penekanan pada pemahaman konsep, kemampuan menghitung, serta penerapan pada kasus nyata (quality control, reliabilitas, inferensi dasar). Adapun Refernsi Perkuliahan ini diambil dari : [1]. R. E. Walpole, R. H. Myers, S. L. Myers, and K. Ye, Probability & Statistics for Engineers & Scientists, 9th Edition, Pearson Education, 2016. [2]. R. D. Yates and D. J. Goodman, Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers, 3rd Edition, Wiley, 2013. [3]. J. L. Devore, Probability and Statistics for Engineering and the Sciences, 9th Edition, Cengage Learning, 2016Course description : I. Concept of Opportunity: Sample Space, Events, Operation to Event, Enumeration of Snippet Points, Event Chances, Law of Chance, Conditional Probability, Bayes Rule II. Random Variables: Concept of Random Variables, Discrete Probability Distributions, Continuous Probability Distributions, Empirical Distributions, Combined Probability Distributions, Expected Values, Expected Value Law, Properties of Variance, Chebyshev Theorem III. Discrete Probability Distribution: Uniform distribution, Binomial and multinomial distribution, Hypergeometric distribution, Poisson distribution, Negative and geometric binomial distribution IV. Continuous Probability Distribution: Normal/Gauss distribution, Areas below normal curve, Normal approximation for binomial distribution, Gamma, Exponential, and Chi-squared distribution, Weibull Distribution V . Functions of Random Variables: Random Variable Transformations, Moment Generator Functions, Random Sampling, Sampling Theory, Mean Scatter Sampling, Scatter Sampling (n-1)S^2/Sigma^2, t-Distribution VI. Estimation Theory: Introduction, Classical Estimation Method, Mean Estimation, Variance Estimation, Estimation Method VII. Hypothesis Test References : [1]. R. E. Walpole, R. H. Myers, S. L. Myers, and K. Ye, Probability & Statistics for Engineers & Scientists, 9th Edition, Pearson Education, 2016. [2]. R. D. Yates and D. J. Goodman, Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers, 3rd Edition, Wiley, 2013. [3]. J. L. Devore, Probability and Statistics for Engineering and the Sciences, 9th Edition, Cengage Learning, 2016