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Analisis Pengaruh Jam Belajar dan Kehadiran terhadap Nilai Ujian Mahasiswa
Penelitian ini bertujuan untuk menganalisis faktor-faktor yang mempengaruhi nilai ujian mahasiswa (Y). Variabel yang digunakan adalah jumlah jam belajar per minggu (X1) dan tingkat kehadiran (X2).
Data yang digunakan terdiri dari 10 mahasiswa yang mencakup nilai ujian, jam belajar, dan persentase kehadiran. Analisis dilakukan menggunakan regresi linier berganda dengan metode Ordinary Least Squares (OLS) untuk mengetahui pengaruh kedua variabel tersebut terhadap nilai ujian.
Hasil analisis diharapkan dapat menunjukkan hubungan antara jam belajar, kehadiran, dan nilai ujian, serta digunakan untuk melakukan prediksi.
Impacto en salud y economia de eventos climáticos
Análisis del impacto de eventos climáticos severos en salud y economía en EE.UU como parte del curso de investigación reproducible en Coursera
投资组合管理作业
倪淑妍 2220232050
4_DBCA_Gemini
4_DBCA_Gemini
Effect of collinearity on the stability and statistical properties of OLS estimators
The objective of this project is to analyze the impact of predictor collinearity on the stability and statistical properties of OLS estimators and the shape of the RSS function.
Mastering the Art of AI Prompting
Develop a comprehensive and practical guide titled “Mastering the Art of AI Prompting.” The guide should be structured, detailed, and suitable for beginners through advanced users. It must include the following components
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The aim of this project is look at various ways to accurately predict measurable minerals used in treatment of drinking water. sample drinking water was tested and recorded for 10 minerals.
"Calcium.CA" "magnesium.Mg" "Sodium.Na" "Potassium"
"Sulfates" "Chlorides" "Nitrates" "Nitrites" "dry.residues"
"Bicarbonates"
##Task
!developed a classification model to identify ideal mineral composition for water treatment using both WHO standards and data-driven approaches. While WHO guidelines served as the foundation benchmark, the decision tree and random forest models provided refined thresholds tailored to the data set.
we shall be comparing the record with WHO standard to determine if those mineral element are present at recommended amount or in excess in our drinking water.
we shall train our model to assist us to easily predict the recommended amount of mineral required.