Want to increase your odds of acing your job interview? If so, brush up on your knowledge of probability theory. In this chapter, we'll roll dice and shoot baskets to explain probabilities using real-life examples.

Discrete distributions

Probability functions

Bernoulli trials

Binomial distribution

Continuous distributions

Uniform distribution

Shape of normal distribution

Sample from normal distribution

Central limit theorem

Law of large numbers

Simulating central limit theorem

Probability Distributions

If the job description appeals to you review descriptive statistics before the interview. In this chapter, you will practice exploratory data analysis (EDA) using natural gas prices and data from a survey analysis.

Descriptive statistics

Centrality measures

Variability measures

Categorical data

Survey analysis

Data encoding

Time series

Time series object

Wrangling time series

Principal Component Analysis

PCA - rotation

PCA - dimension reduction

Exploratory Data Analysis

March confidently into your job interview after reviewing confidence intervals. We'll review the t-test, ANOVA, and normality tests to prepare you for statistics-based coding questions.


Uji normalitas

Uji Shapiro–Wilk

Plot Q-Q

Inferensi untuk sebuah mean

Interval kepercayaan

Uji t satu sampel

Membandingkan dua mean

Uji t dua sampel

Uji berpasangan

ANOVA

Membandingkan kelompok

ANOVA untuk pertumbuhan tanaman

Statistical Tests

Is your potential employer planning to test your R skills? Make sure you’re prepared and practice model evaluation beforehand. In this chapter, we will fit and evaluate linear and logistic regression models using various biomedical datasets. By the end of this chapter, you’ll be fully prepared to answer any question the interviewer throws your way!

Covariance and correlation

Covariance by hand

Linear relationship

Nonlinear relationship

Linear regression model

Fitting linear models

Predicting with linear models

Logistic regression model

Fitting logistic models

Predicting with logistic models

Model evaluation

Validation set approach

Regression evaluation

Classification evaluation

Wrapping up

Regression Models

Natural Gas

Gold monthly

Parkinson's Data

Letter Recognition

Siap untuk wawancara kerja? Anda mungkin sudah memahami segala hal tentang perusahaan incaran, tetapi apakah Anda sudah berlatih pertanyaan wawancara statistik R yang klasik? Jika belum, kami siap membantu. Di kursus ini, Anda akan mempersiapkan topik-topik statistik yang paling sering dibahas, mulai dari distribusi hingga pengujian hipotesis, model regresi, dan banyak lagi. Anda akan mengasah keterampilan menggunakan himpunan data termasuk data penyakit Parkinson dan harga gas. Kursus ini sengaja dibuat lebih menantang daripada kursus DataCamp pada umumnya agar saat waktu wawancara tiba Anda siap menjawab dengan percaya diri setiap pertanyaan wawancara statistik di R.

Intermediate R

Foundations of Inference in R

Foundations of Probability in R

Dalam kursus ini, Anda akan mempelajari topik statistik seperti distribusi, uji hipotesis, dan regresi.

Latihan Pertanyaan Wawancara Statistik di R

Uji t satu sampel

Latihan Pertanyaan Wawancara Statistik di R

Latihan interaktif praktis