Hello,
I'm looking for a R programmer that can handle the analysis of a dataset.
What I need is the analysis of an Y (dependant) variable of this dataset using regression or classification methods:
Task needed in case of regression:
• preliminar screening with eg VIF and correlation analysis
• regression best subset, stepwise f b,
• ridge and lasso reg
• PCA
• prediction
Tasks needed in ccase of classification:
• preliminar screening (eg boxplot)
• logistic reg (glm binomial)
• LDA, QDA
• KNN
• cross validation for each method
I'm a student and the work is for "didactic purposes", it should be clean and understandable by a "basic user", with an output that can be put on a presentation poster.
Whatever Y is good for us (we think that symboling or [login to view URL] can be good Y but we are open to new ideas!)
Hope to ear from you as soon as possible, I have a deadline the 3th of december.
Here you find the dataset
"[login to view URL]"
"[login to view URL]"
description: "[login to view URL]"
if you can, plase answer in italian.
R Expert with more than 4+ years of experience. I have been doing descriptive and inferential statitistics
Key Techniques are
Regression Model
Binary Logistic Model
Factor Analysis
Cluster Analysis
Neural Network
Parametric and Non-Parametric Test
Good in data visualization using Data mining technique like CRT,QUESTetc
Please refer my client's feedback ( 5 star rated) Kindly reach out to me for further discussions