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Course Outline
Statistics & Probabilistik Programming di Julia
Statistik dasar
- Statistics
- Ringkasan Statistics dengan paket statistik
- Paket Distribusi & StatsBase
- Univariat dan multivariat
- Momen
- Fungsi probabilitas
- Pengambilan sampel dan RNG
- Histogram
- Estimasi kemungkinan maksimum
- Produk, penyuluhan, dan distribusi tersensor
- Statistik yang kuat
- Korelasi & kovariansi
Bingkai Data
(Paket DataFrames)
- Data masukan/keluaran
- Membuat Bingkai Data
- Tipe data, termasuk data kategorikal dan data yang hilang
- Menyortir & bergabung
- Membentuk ulang & memutarbalikkan data
Pengujian hipotesis
(Paket Uji Hipotesis)
- Garis besar prinsip pengujian hipotesis
- Uji Chi-Kuadrat
- uji z dan uji t
- Uji F
- Uji pasti Fisher
- Analisis Varians
- Uji normalitas
- Uji Kolmogorov-Smirnov
- Uji T Hotelling
Analisis regresi & kelangsungan hidup
(Paket GLM & Survival)
- Prinsip garis besar regresi linier dan keluarga eksponensial
- Regresi linier
- Model linier umum
- Regresi logistik
- Regresi Poisson
- Regresi gamma
- Model GLM lainnya
- Analisis kelangsungan hidup
- Acara
- Kaplan Meier
- Nelson Aalen, seorang petani
- Bahaya Proporsional Cox
Jarak
(Paket jarak)
- Apa itu jarak?
- Bahasa Euklides
- Blok Kota
- Kosinus
- Korelasi
- Mahalanobis
- Berpura-pura
- GILA
- RMS
- Deviasi kuadrat rata-rata
Statistik multivariat
(Paket MultivariateStats, Lasso, & Loess)
- Regresi punggungan
- Regresi laso
- Biji loess
- Analisis diskriminan linier
- Analisis Komponen Utama (PCA)
- PCA Linier
- Kernel PCA
- PCA Probabilistik
- CA Independen
- Regresi Komponen Utama (PCR)
- Analisis Faktor
- Analisis Korelasi Kanonik
- Skala multidimensi
Kekelompokan
(Paket pengelompokan)
- K-berarti
- K-medoid
- DBSCAN
- Pengelompokan hierarkis
- Algoritma Markov Cluster
- Pengelompokan C-means fuzzy
Bayesian Statistics & Probabilistik Programming
(Paket Turing)
- Model Rantai Markov Carlo
- Montel Carlo ala Hamilton
- Model Campuran Gaussian
- Regresi Linier Bayesian
- Regresi Keluarga Eksponensial Bayesian
- Bahasa Bayesian Neural Networks
- Model Markov Tersembunyi
- Penyaringan Partikel
- Inferensi Variasional
Requirements
Kursus ini ditujukan bagi orang-orang yang sudah memiliki latar belakang dalam ilmu data dan statistik.
21 Hours
Testimonials (5)
Variasi dengan latihan dan pertunjukan.
Ida Sjoberg - Swedish National Debt Office
Course - Econometrics: Eviews and Risk Simulator
Machine Translated
the trainer had patience, and was eager to make sure we all understood the topics, the classes were fun to attend
Mamonyane Taoana - Road Safety Department
Course - Statistical Analysis using SPSS
Day 1 and Day 2 were really straight forward for me and really enjoyed that experience.
Mareca Sithole - Africa Health Research Institute
Course - R Fundamentals
The pace was just right and the relaxed atmosphere made candidates feel at ease to ask questions.
Rhian Hughes - Public Health Wales NHS Trust
Course - Introduction to Data Visualization with Tidyverse and R
Michael the trainer is very knowledgeable and skillful about the subject of Big Data and R. He is very flexible and quickly customize the training meeting clients' need. He is also very capable to solve technical and subject matter problems on the go. Fantastic and professional training!.
