I will work on r,SAS and python projects

Data is definitely the new oil and having the best techniques for data analysis enables reliable decision making in different organizations or businesses. There are many statistical methods that can be used to make sense out of data. Among the common statistical approaches used by researchers are descriptive analytics, explorative analysis, ANOVA, MANOVA, regression, correlation analysis, meta-analyses, process analysis, ML such as SVM, Decision trees, RFs (Random Forests), and various other machine learning algorithms. The good news is that advanced statistical software such as R has customized statistical packages such as MASS, tidy verse, e1071, ggplots, etc which make it very easy to analyze any type of data. R statistical software also provides for reliable visualization tools such as R-shiny. It also enables easy presentation using R-markdown or R slides.

I have extensive experience in not only data analysis and modeling but also in proficient usage of R to perform different statistical analyses e.g.

1. Machine Learning model creations
2. Data Manipulation
3. Descriptive analysis
4. Exploratory data analysis
5. ANOVA
6. MANOVA
7. Regression
8. SVM
9. RFs
10. Predictive modeling
11. Data classification