Statistical Programming

STAT 4510: Applied Statistical Models

STAT 4002: Regression with R Programming

INFOTEC : Intro to Python Programming

STAT 4110: Statistical Software and Data Analysis

CMPSC 1040: Intro to C Programming

COURSE DESCRIPTIONS:

• Data Management Techniques

• Statistical Analysis

• ANOVA

• Non-Parametric Analysis

• Descriptive Statistics

• R/R-Studio/C/SAS 9.4/SAS JMP/Python in Jupyter Notebook

• Supervised Learning

• Experimental Design

• Intro to C Programming

HOW IS IT USEFUL IN DATA SCIENCE?

• Data wrangling and manipulation are requirements to succeed in data science. As I learned these analytical tools, I had more weapons to use to my advantage to tackle real world data problems. By learning multiple languages, I was taught to learn a tool in its entirety and that the logic behind each tool is valuable to learn the next. My favorite tool is R-Studio. Learn more about it here.