Pengantar Pemrograman R: Dari Skrip ke Pemrograman

Transisi dari skrip ke pemrograman di R menandai pergeseran dari menjalankan pernyataan interaktif yang terpisah-pisah menjadi membangun pipeline otomatis dan skalabel. Evolusi ini melibatkan pengorganisasian data ke dalam wadah yang kuat seperti vektor, matriks, faktor, larik, dan daftar untuk menangani arsitektur informasi yang kompleks.

1. Alur Kontrol Program

Alih-alih pengulangan manual, kita menggunakan blok logika untuk mengelola kompleksitas. R menyediakan mekanisme alur kontrol terstruktur:

Iterasi:for (nama dalam expr_1) expr_2, while (kondisi) expr, dan ulangi expr.
Kondisional:if (expr_1) expr_2 else expr_3 untuk percabangan logika dan fungsi vektorisasi ifelse untuk keputusan elemen demi elemen.

# Pengelompokan ekspresi
{ expr_1 ; ... ; expr_m }

2. Berpikir Vektorisasi & Pemetaan Fungsional

Pemrograman di R memanfaatkan iterasi fungsional untuk memproses struktur data tanpa loop eksplisit. Fungsi seperti apply, lapply, sapply, dan tapply memungkinkan Anda memetakan logika pada larik atau daftar. Sebagai contoh, menggunakan split untuk mengelompokkan kerangka data berdasarkan faktor dan kemudian menerapkan rata_rata, var, atau akar_pangkat(jumlah(x)) perhitungan secara signifikan mengurangi utang kode dan kesalahan.

TERMINALbash — 80x24

> Ready. Click "Run" to execute.

QUESTION 1

Which structure allows you to group multiple R expressions into a single logical block?

( expr_1 , expr_2 )

{ expr_1 ; ... ; expr_m }

block[ expr_1 ]

list( expr_1 )

✅ Correct!

Braces {} are used to group multiple statements into one expression, often used in function bodies or loops.

❌ Incorrect

R uses curly braces {} to encapsulate a multi-line code block.

QUESTION 2

When would a programmer choose lapply over a standard for loop?

When the data is stored in a matrix only.

To explicitly use lsfit on single vectors.

To apply a function to each element of a list and return a list.

To stop execution immediately via repeat.

✅ Correct!

lapply is the functional way to iterate over lists, returning a result of the same length.

❌ Incorrect

lapply stands for 'list apply' and is part of R's functional programming toolkit.

QUESTION 3

What is the primary advantage of using for (i in 1:length(yc)) in the context of linear regression on multiple sets?

It automatically calculates the mean of xc.

It ensures logic remains concise regardless of the number of datasets.

It converts a list into a factor.

It forces the use of ifelse for plotting.

QUESTION 4

How does ifelse differ from if...else?

ifelse is used only inside repeat loops.

if...else is vectorized, while ifelse is not.

ifelse is vectorized; if...else handles only a single logical value.

There is no difference in R.

✅ Correct!

ifelse can process whole vectors at once, whereas if expects a single TRUE/FALSE.

❌ Incorrect

if is for control flow; ifelse is a vectorized function.

QUESTION 5

Which function would you use to group data by categories before applying a summary statistic like sum?

split

lsfit

abline

sqrt

✅ Correct!

split divides data into groups based on a factor, which can then be processed by the apply family.

❌ Incorrect

split is essential for 'Split-Apply-Combine' workflows in R.