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LAB1 - SAD - UOC
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R Markdown analysis identifying key revenue drivers using Random Forest feature importance and logistic regression. Includes correlation heatmaps, variable importance plots, and styled tables. Built with ggplot2, randomForest, and kableExtra. Synthetic B2B SaaS deal data included.
Simulation of Random Variables: Discrete and Continuous Distributions
Simulation of Random Variables: Discrete and Continuous Distributions
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Linear Regression Modeling
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R Markdown lead scoring model using logistic regression and Random Forest to predict conversion likelihood. Includes ROC curves, feature importance ranking, and score-tiering logic. Built with ggplot2, randomForest, and kableExtra. Synthetic lead data included.
Analisis Hubungan Kecepatan Mobil Terhadap Pengereman Menggunakan Model Regresi Linear
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Discount Elasticity & Price Sensitivity Analysis
R Markdown analysis measuring the impact of discounting on win rates and deal margins. Models price elasticity across segments and product lines using regression and grouped comparisons. Built with ggplot2 and kableExtra. Synthetic B2B deal data included.