An introduction to key parts of experimental design plus some power and sample size calculations.

Pengantar desain eksperimental

Eksperimen dasar

Pengacakan

Replikasi dan pemblokiran

Replikasi

Blocking

Pengujian hipotesis

Uji satu sisi vs. dua sisi

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Perhitungan Daya & Ukuran Sampel

Introduction to Experimental Design

Explore the Lending Club dataset plus build and validate basic experiments, including an A/B test.

ANOVA, single, and multiple factor experiments

Exploratory Data Analysis (EDA) Lending Club

How does loan purpose affect amount funded?

Which loan purpose mean is different?

Multiple Factor Experiments

Model validation

Pre-modeling EDA

Post-modeling validation plots + variance

Kruskal-Wallis rank sum test

A/B testing

Which post-A/B test test?

Sample size for A/B test

Basic A/B test

A/B tests vs. multivariable experiments

Basic Experiments

Use the NHANES data to build a RCBD and BIBD experiment, including model validation and design tips to make sure the BIBD is valid.

Intro to NHANES and sampling

NHANES dataset construction

NHANES EDA

NHANES Data Cleaning

Resampling NHANES data

Randomized Complete Block Designs (RCBD)

Which is NOT a good blocking factor?

Drawing RCBDs with Agricolae

NHANES RCBD

RCBD Model Validation

Balanced Incomplete Block Designs (BIBD)

Is a BIBD even possible?

Drawing BIBDs with agricolae

BIBD - cat's kidney function

NHANES BIBD

Randomized Complete and Balanced Incomplete Block Designs

Evaluate the NYC SAT scores data and deal with its missing values, then evaluate Latin Square, Graeco-Latin Square, and Factorial experiments.

Latin squares

NYC SAT Scores EDA

Dealing with Missing Test Scores

Drawing Latin Squares with agricolae

Latin Square with NYC SAT Scores

Graeco-Latin squares

NYC SAT Scores Data Viz

Drawing Graeco-Latin Squares with agricolae

Graeco-Latin Square with NYC SAT Scores

Factorial experiments

NYC SAT Scores Factorial EDA

Factorial Experiment with NYC SAT Scores

Evaluating the NYC SAT Scores Factorial Model

What's next in experimental design?

Latin Squares, Graeco-Latin Squares, and Factorial Experiments

sample of Lending Club data

NHANES Body Measures

NHANES Demographics

NHANES final combined dataset

NHANES Medical Conditions

NYC SAT Scores

Perancangan eksperimen merupakan bagian krusial dari analisis data di bidang apa pun, baik bisnis, kesehatan, maupun teknologi. Jika Anda ingin menggunakan data untuk menjawab pertanyaan, Anda perlu merancang sebuah eksperimen! Dalam kursus ini Anda akan mempelajari dasar-dasar perancangan eksperimen, termasuk rancangan blok dan faktorial, serta uji statistik yang umum digunakan seperti uji t dan ANOVA. Anda akan menggunakan data bawaan R dan himpunan data dunia nyata termasuk survei CDC NHANES, Nilai SAT dari Sekolah Umum NY, dan Data Pinjaman Lending Club. Setelah mengikuti kursus ini, Anda akan mampu merancang dan menganalisis eksperimen Anda sendiri!

Hypothesis Testing in R

Pelajari desain eksperimen dasar, termasuk blok dan faktorial, serta uji statistik t dan ANOVA di R.

Perancangan Eksperimen di R

Dalam kursus ini, Anda akan mempelajari tentang desain eksperimen dasar, yang merupakan bagian penting dari analisis data.

Associate Data Scientist di R

Ahli Statistik di R

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Perancangan Eksperimen di R

Latihan interaktif praktis