05:41

Menuju Jakarta 100% vaksinasi COVID_penerapan Data Mining

12:21

Optimalisasi Kinerja Pencegahan Korupsi di Indonesia

23:38

Prediksi laju perkembangan ekspor kacang kedelai di Indonesia dengan metode Long Short Term Memory

10:01

Pre-processing data: contoh kasus penggunaan energi.

09:57

Contoh pre-processing data

07:43

Pre_processing data: Tugas 1 kuliah Eksplorasi dan Visualisasi Data

09:03

Grand Prix Formula E 2022 dalam cuitan warga

06:56

Kamu suka streaming? Simak ini dulu yuk :)

09:56

Switch over Manggarai: bagaimana opini publik?

05:54

Johnny Depp versus Amber Heard: kamu tim siapa nih?

09:33

Mau ke Borobudur tapi mahal?

05:42

Tren twit terkait hilangnya Emmeril Khan

06:31

Suka film horor? Simak dulu deh hasil analisis anak statistika tentang film KKN di Desa Penari ini

05:15

Indonesia Masters 2022 dalam kacamata Statistika

08:48

Bagaimana budaya literasi di Amerika? Simak analisisnya yuk

07:36

Pecinta drakor merapat. Anak Statistik mau kasih analisis nih :)

08:08

Variable selection (3/5): forward selection

06:20

Variable selection (4/5): stepwise procedure

08:42

Logistic regression (1/3): Searching for a link function

05:08

Logistic regression (2/3): Modelling the probability of success

08:37

Logistic regression (3/3): Odds ratio interpretation

07:01

Residual analysis (4/4): checking normality assumption

10:38

Residual analysis (3/4): Detecting heteroscedasticity

11:23

Residual analysis (2/4): checking model fit

11:59

Residual analysis (1/4): motivation

12:09

Multicollinearity (1/2): math concept

10:45

Variable selection (5/5): Cons for stepwise procedure

09:27

Multicollinearity (2/2): illustration

10:21

Regression Errors and residuals

09:53

Testing the Goodness of Fit of the Model

07:57

Testing the Goodness of Fit of the Model R output example

13:21

Coefficient of correlation (1/2)

09:20

Coefficient of correlation (2/2): its relation with regression

11:56

Model building: Overview

08:18

Model validation (1/2): motivation

12:01

Model validation (2/2): procedure and metrics

10:37

Multiple regression: A model with numerical predictors

09:57

Multiple regression: A model with categorical predictors

07:21

Variable selection (2/5): backward elimination

04:09

Variable selection (1/5): Overview

09:38

Week 3: Model assumption_part 2_normality

09:39

Week 3: Model assumption_part 1_zero mean error

10:51

Week 2: Linear vs non linear model

07:51

Intro to linear model (3/3): observational versus experimental

11:23

Intro to linear model (2/3): data types

08:59

Intro to linear model (1/3): some examples

02:03:47

Kuliah Umum untuk Guru SMA: Distribusi Peluang

05:46

Profil Prodi Sarjana Statistika FMIPA UI

09:28

Distribusi variabel acak diskrit (6/6)

09:18

Distribusi variabel acak diskrit (5/6)

11:18

Distribusi variabel acak diskrit (4/6)

08:25

Distribusi variabel acak diskrit (2/6)

08:54

Distribusi variabel acak diskrit (3/6)

09:37

Distribusi variabel acak diskrit (1/6)

09:17

Data Mining 10 - Pendahuluan Supervised Learning (Model Klasifikasi) (4/5)

04:44

Data Mining 10 - Pendahuluan Supervised Learning (Model Klasifikasi) (5/5)

10:01

Data Mining 10 - Pendahuluan Supervised Learning (Model Klasifikasi) (3/5)

10:02

Data Mining 10 - Pendahuluan Supervised Learning (Model Klasifikasi) (2/5)

10:00

Data Mining 10 - Pendahuluan Supervised Learning (Model Klasifikasi) (1/5)

09:15

Data Mining 09 - Korelasi & Analisa Regresi (3/3)