Data Leakage in R: Why Correct Evaluation Matters Even When Metrics Do Not Change
Data Leakage
R Programming
Data Preprocessing
Model Evaluation
Statistical Learning
Machine Learning Pitfalls
Reproducible Research
A model that performs exceptionally well on a test set is not necessarily a good model; in many cases, it is a warning sign. High accuracy or low error metrics are…
M. Fatih Tüzen
Jan 22, 2026

Data Normalization in R: When, Why, and How to Scale Your Data Correctly
Data Preprocessing
R Programming
Data Science
Machine Learning
This article is part of a broader series on data preprocessing in R. In earlier posts, we focused on two problems that quietly ruin analyses long before modeling begins: miss…
M. Fatih Tüzen
Jan 2, 2026

Understanding Data Import and Export in R: Working with CSV and Excel Files
R Programming
Data Analysis
Data Science
CSV
Excel
Data Import
Data Export
When learning R, most people focus on functions, models, and visualizations. However, many real-world problems start much earlier — at the data import stage — and end much…
M. Fatih Tüzen
Dec 26, 2025

Outliers in Data Analysis: Detecting Extreme Values Before Modeling in R with İstanbul Airbnb Data
R
Statistics
Data Analysis
Data Science
Data Preprocessing
Outliers
Inter Quartile Range
Z-Score
Data Cleaning
Data preprocessing is often presented as a sequence of technical steps. However, each preprocessing decision implicitly embeds a statistical assumption.
M. Fatih Tüzen
Dec 19, 2025

Handling Missing Data in R: A Comprehensive Guide
R
Statistics
Data Analysis
Data Science
Data Preprocessing
Missing Data
Data Cleaning
Imputation
Data preprocessing is a cornerstone of any data analysis or machine learning pipeline. Raw data rarely comes in a form ready for direct analysis — it often requires…
M. Fatih Tüzen
Aug 18, 2025

Standard Deviation vs. Standard Error: Meaning, Misuse, and the Math Behind the Confusion
R
Statistics
Data Analysis
Standard Deviation
Standard Error
In the world of data analysis and statistics, standard deviation (SD) and standard error (SE) are two concepts that are often misunderstood or—worse—used interchangeably.…
M. Fatih Tüzen
Jul 11, 2025

Correlation vs Causation: Understanding the Difference
Statistics
Correlation
Causation
Econometrics
Causal Inference
Public Health
“Correlation is not causation” – it’s a refrain we hear often, yet the distinction between these concepts is deceptively easy to overlook. Correlation refers to a…
M. Fatih Tüzen
Jun 4, 2025

Explained vs. Predictive Power: R², Adjusted R², and Beyond
R
Statistics
Machine Learning
r-squared
adjusted-r-squared
predictive-modeling
tidymodels
model-evaluation
You trust R². Should you?
You proudly present a model with R² = 0.95. Everyone applauds.
But what if your model fails miserably on the next new data?
M. Fatih Tüzen
Apr 30, 2025

Underrated Gems in R: Must-Know Functions You’re Probably Missing Out On
reduce
vapply
do.call
clean_names
R is packed with powerhouse tools—think dplyr for data wrangling, ggplot2 for stunning visuals, or tidyr for tidying up messes. But beyond the headliners, there’s a lineup…
M. Fatih Tüzen
Mar 11, 2025

Unlocking CBRT Data in R: A Guide to the CBRT R Package
R Programming
CBRT
EVDS
Import
API
The Central Bank of the Republic of Turkey (CBRT) provides a wealth of economic data crucial for researchers, analysts, and policymakers. Through the Electronic Data…
M. Fatih Tüzen
Dec 31, 2024

Extracting Data from OECD Databases in R: Using the oecd and rsdmx Packages
R Programming
OECD
rsdmx
Import
API
The OECD (Organisation for Economic Co-operation and Development) provides extensive databases for economic, social, and environmental indicators. Accessing these…
M. Fatih Tüzen
Dec 16, 2024

Creating Professional Excel Reports with R: A Comprehensive Guide to openxlsx Package
R Programming
Report Automation
openxlsx
Excel
The ability to generate professional Excel reports programmatically is a crucial skill in data analysis and business reporting. In this comprehensive guide, we’ll explore…
M. Fatih Tüzen
Nov 4, 2024

Artwork by: Allison Horst

Mastering Date and Time Data in R with lubridate
R Programming
lubridate
time series
time manipulation
date handling
lubridate is a powerful and widely-used package in the tidyverse ecosystem, specifically designed for making date-time manipulation in R both easier and more intuitive. It…
M. Fatih Tüzen
Sep 30, 2024

Artwork by: Shannon Pileggi and Allison Horst

Mastering Data Transformation in R with pivot_longer and pivot_wider
R Programming
tidyr
pivot_wider
pivot_longer
data transformation
Data analysis requires a deep understanding of how to structure data effectively. Often, datasets are not in the format most suitable for analysis or visualization. That’s…
M. Fatih Tüzen
Sep 19, 2024

Text Data Analysis in R: Understanding grep, grepl, sub and gsub
R Programming
grep
grepl
sub
gsub
regex
text analysis
In text data analysis, being able to search for patterns, validate their existence, and perform substitutions is crucial. R provides powerful base functions like grep, grepl, …
M. Fatih Tüzen
Jul 9, 2024

Exploring apply, sapply, lapply, and map Functions in R
R Programming
apply
sapply
lapply
map
In R programming, Apply functions (apply(), sapply(), lapply()) and the map() function from the purrr package are powerful tools for data manipulation and analysis. In this…
M. Fatih Tüzen
Apr 15, 2024

R Function Writing 101:A Journey Through Syntax, Best Practices, and More
R Programming
Functions
R is a powerful and versatile programming language widely used in data analysis, statistics, and visualization. One of the key features that make R so flexible is its…
M. Fatih Tüzen
Jan 23, 2024

https://allisonhorst.com/everything-else

Cracking the Code of Categorical Data: A Guide to Factors in R
R Programming
data types
factor
categorical data
R programming is a versatile language known for its powerful statistical and data manipulation capabilities. One often-overlooked feature that plays a crucial role in…
M. Fatih Tüzen
Jan 11, 2024

https://openscapes.org/blog/2020-10-12-tidy-data/

Unraveling DataFrames in R: A Comprehensive Guide
R Programming
data types
dataframe
tibble
In R, a data frame is a fundamental data structure used for storing data in a tabular format, similar to a spreadsheet or a database table. It’s a collection of vectors of…
M. Fatih Tüzen
Dec 29, 2023

Understanding Lists in R Programming
R Programming
data types
lists
R, a powerful statistical programming language, offers various data structures, and among them, lists stand out for their versatility and flexibility. Lists are collections…
M. Fatih Tüzen
Dec 19, 2023

https://www.vectorstock.com/royalty-free-vector/green-matrix-numbers-cyberspace-with-vector-24906241

Understanding Matrices in R Programming
R Programming
data types
matrices
Matrices are an essential data structure in R programming that allows for the manipulation and analysis of data in a two-dimensional format. Understanding their creation…
M. Fatih Tüzen
Nov 20, 2023

Exploring Vectors in R Programming: The Fundamental Building Blocks
R Programming
data types
vectors
In the realm of R programming, vectors serve as the fundamental building blocks that underpin virtually every data analysis and manipulation task. Much like atoms are the…
M. Fatih Tüzen
Oct 3, 2023

Understanding Data Types in R
R Programming
data types
Learning R programming is akin to constructing a sturdy building. You need a powerful foundation to support the structure. Just as a building’s foundation dictates its…
M. Fatih Tüzen
Sep 26, 2023

A Gentle Introduction to R Programming
R Programming
R Studio
Hello everyone! For my first post on my blog, I would like to make an introduction about R. Before we start coding with R, it’s not a bad idea to know a little about this…
M. Fatih Tüzen
Aug 15, 2023
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