Down-to-earth statistics for research and decisions
Notes on data analysis, theses, and reading numbers honestly. Our English articles are below, and we are translating more. Older articles are still in Indonesian.
Articles in English
Down-to-earth statistics, in English.
Social Media Polls vs. Random Surveys: Understanding Selection Bias Before Making Decisions
In recent years, I have increasingly heard remarks like this in meetings: “We ran an Instagram poll yesterday, and 80% of our followers agreed.” Or: “Our customer…
Age, Period, and Cohort Effects: Why the “Lazy Gen Z” Claim Fails the Statistical Test
In nearly every workplace I visit for analytics work, a familiar phrase surfaces whenever discussions turn to younger staff: “Younger workers today are just…
Unemployment Rates by Education: How to Present Group Comparisons Honestly
There is one chart that almost inevitably makes the rounds every time Statistics Indonesia (BPS) releases labor force figures: the bar chart showing unemployment rates…
Reading the Open Unemployment Rate: Definitions, Denominators, and Common Pitfalls
Every time the Central Statistics Agency (BPS) publishes labor force data, one number immediately floods chat groups and social media timelines. For February 2026, that…
Only 20.28% of Victims Report: From Understanding the Dark Figure of Crime to Taking Action
A few weeks ago I wrote that only about one in five crime victims reports to the police. Since then, many people have asked the same question: “Okay,…
Weekly Recap: 7 Lessons on Reading Data from a Week of Unpacking Numbers
Sunday morning is a good time to pause and ask: what did we actually learn this week? Since Monday, 19 October, we’ve unpacked numbers from seven different angles…
Ask a Criminologist: 4 Questions People Always Ask When Reading Crime Statistics
This morning I answered questions about sample size, normality, and p-values. This afternoon it’s the turn of the questions that come up every time people read crime…
Ask a Statistician: 3 Questions I Get Asked the Most (and My Honest Answers)
Three statistics questions students and researchers ask the most: how large a sample is enough, does non-normal data require a non-parametric test, and does a non-significant result mean…
5 Misconceptions About Official Statistics (and How to Avoid Being Misled)
Category: Data literacy · Series “Reading Indonesian Numbers” #1 · Source: BPS, Crime Statistics 2024
“85% Accurate” Employee Attrition Prediction: Why That Number Can Be Misleading and What to Look For Instead
Imagine a vendor pitching to your HR leadership. “Our turnover prediction model boasts 85% accuracy.” Heads nod around the conference table. It sounds convincing, right?…
4,149 Environmental Crime Incidents, 32% in One Province: Does That Mean North Sumatra Is the “Most Damaged”?
When you picture crime, what usually comes to mind is theft, fraud, or violence. Few people immediately think of forests cleared without permits, fish poached from the…
17.17% of Citizens Admit Paying “Extra Money” for Public Services: Reading the Anti-Corruption Behavior Index
We usually picture corruption as something huge: billions in value, senior officials, a courtroom full of cameras. But there is another side to corruption that is far…
More articles (in Indonesian)
These articles are written in Indonesian.
Polling media sosial vs survei acak: memahami bias seleksi sebelum mengambil keputusan
Beberapa tahun terakhir, saya makin sering mendengar kalimat seperti ini di rapat: “Kemarin kita polling di Instagram, 80% pengikut setuju.” Atau: “Grup WhatsApp…
Grafik pengangguran menurut pendidikan: cara menyajikan data kelompok dengan jujur
Ada satu grafik yang hampir pasti muncul setiap BPS merilis data ketenagakerjaan: grafik batang tingkat pengangguran menurut pendidikan. Grafik ini sering dibagikan…
Membaca tingkat pengangguran terbuka: definisi, penyebut, dan jebakan yang sering terjadi
Setiap kali BPS merilis data ketenagakerjaan, ada satu angka yang langsung beredar di grup percakapan dan media sosial. Untuk Februari 2026, angka itu adalah tingkat…
Hanya 20,28% Korban yang Melapor: Dari Memahami Angka Gelap ke Tindakan yang Bisa Dilakukan
Beberapa pekan lalu saya menulis bahwa hanya sekitar seperlima korban kejahatan yang melapor ke polisi. Setelah itu banyak yang bertanya hal yang sama: “Oke, saya paham…
Rangkuman Satu Pekan: 7 Pelajaran Membaca Data dari Tujuh Hari Membongkar Angka
Minggu pagi adalah waktu yang enak untuk berhenti sebentar dan bertanya: apa sebenarnya yang kita pelajari sepekan ini? Sejak Senin 19 Oktober, kita membongkar angka…
Tanya Kriminolog: 4 Pertanyaan yang Sering Muncul Saat Orang Membaca Statistik Kriminal
Pagi tadi saya menjawab pertanyaan seputar sampel, normalitas, dan nilai p. Sore ini giliran pertanyaan-pertanyaan yang muncul setiap kali orang membaca statistik…
Tanya Statistikawan: 3 Pertanyaan yang Paling Sering Saya Terima (dan Jawaban Jujurnya)
Tiga pertanyaan statistik yang paling sering ditanyakan mahasiswa dan peneliti: berapa sampel yang cukup, apakah data tidak normal harus non-parametrik, dan apakah hasil tidak signifikan berarti gagal. Jawaban…
5 Salah Paham tentang Angka Resmi (dan Cara Membacanya Supaya Tidak Gampang Tertipu)
Ada satu kalimat yang sering saya dengar di ruang rapat, di kolom komentar, bahkan di ruang sidang skripsi: “Tapi ini kan data resmi.” Kalimat itu dipakai sebagai palu…
Model Prediksi Karyawan Resign “Akurasi 85%”: Kenapa Angka Itu Bisa Menyesatkan, dan Apa yang Harus Dilihat
Bayangkan seorang vendor presentasi di depan tim SDM. “Model prediksi turnover kami memiliki akurasi 85%.” Ruangan mengangguk. Kedengarannya mengesankan, bukan? Delapan…
4.149 Kejadian Kejahatan Lingkungan, 32% di Satu Provinsi: Apakah Itu Berarti Sumatera Utara “Paling Rusak”?
Kalau kamu membayangkan kejahatan, mungkin yang terlintas adalah pencurian, penipuan, atau kekerasan. Jarang yang terpikir tentang hutan yang ditebang tanpa izin, ikan…
17,17% Warga Mengaku Pernah Memberi “Uang Tambahan” Saat Mengurus Layanan Publik: Membaca Indeks Perilaku Anti Korupsi
Korupsi biasanya kita bayangkan sebagai hal yang besar: nilai miliaran, pejabat tinggi, ruang sidang dengan kamera berjejer. Tapi ada sisi lain dari korupsi yang jauh…