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Actively open-minded thinking -all items - WNM-C
EGA plot - AOT data - all items - WNM condition - contiguous order
Actively open-minded thinking -all items - WNM-R
EGA plot - AOT data - all items - WNM condition - random order
CASO 28 MUESTREO Y TIPOS DE MUESTREO
CASO 28 MUESTREO Y TIPOS DE MUESTREO
Actively open-minded thinking - original items - WNM-R
EGA plot - AOT original items only - WNM condition - random order
Actively open-minded thinking - original items - WNM-C
EGA plot - original items only - WNM condition - contiguous order
Skincare Ingredient Analysis by Product Type
This project analyzes common ingredients across five major skincare product categories—Cleanser, Toner, Moisturiser, SPF, and Serum—using a dataset of product ingredients. It identifies the top ingredients within each category and explores frequent ingredient pairings to reveal formulation patterns. The analysis aims to provide insights into product development trends and help consumers understand typical ingredient combinations in skincare. Data sourced from a public Kaggle dataset.
H3
Simple Linear Regression