This RMD covers concepts such as backshift notation and polynomial roots which are important for causality and invertibility.

Examples of ACF and PACF plots.

This RMD gives an introduction to how functional programming can be utilized within the big data context.

Visualization of how to find the MLE given a distribution.

Intro to SLR.

Markdown from the HW 4 from my university's Statistical Data Science course.

This is the markdown for the code used in the first homework assignment from STA 141A at UC Davis with Prof. Gupta.

From the first assignment in Prof. Gupta's STA 141A course titled, 'Statistical Data Science.' In the first homework we were asked to analyze a dataset using R that consisted of different college data.

The R Markdown for code used in the lesson titled, 'Linear Regression pt.2.'

A markdown of some indices with technical indicators

This is the final project for STA 108 with Prof. Chen, Fall '17 at U.C. Davis. The project involved performing regression on a response variable using 16 predictors. Data was split for the purpose of cross-validation. Several criteria were tested, along with using forward stepwise regression on a model. In the end, a model was selected according to MSPR.

The R markdown for a project done for STA 108, Prof. Chen Fall '17 at U.C. Davis.