Code-Based Analysis

R & Python Statistical Analysis

Get clean, reproducible data science pipelines. I structure RStudio scripts and Jupyter Notebook workflows that deliver transparent statistical results and high-resolution plots.

R and Python Scripting Illustration

Academic integrity notice: I write custom scripts for data cleaning, statistic models, and visualization plotting. I do not fabricate code outputs, forge dataset variables, or complete academic submissions dishonestly.

Script Environments

Reproducible Statistical Pipelines

Need transparent, script-based data analysis? I structure clean code workflows in R and Python to make your research fully reproducible.

1. Data Wrangling & Cleaning

I structure custom scripts using `tidyverse` (R) or `pandas` and `numpy` (Python) to read raw datasets, sort variables, filter observations, handle missing values, and scale indices.

2. Reproducible Workflows

You receive fully-documented R scripts (.R) or Jupyter Notebooks (.ipynb) containing well-commented code, enabling any reviewer or advisor to replicate your calculations instantly.

3. Hypothesis & Statistical Testing

I configure statistical models using `stats` (R) or `statsmodels` and `scipy` (Python): linear regression, logistic classification, ANOVA tables, chi-square cross-tabulations, and correlation matrices.

4. Premium Visualizations

I produce high-resolution, publication-ready plots. I utilize `ggplot2` (R) or `matplotlib` and `seaborn` (Python) to export customized histograms, correlation plots, and regression fits.

5. Advanced Modeling

If your study extends beyond standard descriptives, I configure factor analysis (PCA), dimension reduction, cluster grouping, or basic machine learning classifiers using `scikit-learn` or `caret`.

6. Summary Results Reports

Beside raw code files, I provide clear summary reports containing compiled tables, output charts, and written explanations of the statistical parameters (coefficients, p-values, R-squared values).

Looking for code-based data analysis?

Submit your project requirements today. Detail your hypotheses, sample variables, target programming language, and deadline. I will review your request and send an email proposal.

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