# Ma 415: Regression & Time Series

Linear regression, linear time series analysis, development and evaluation of regression and time series models, and forecasting. Exposure to a common analysis software package. Prerequisite(s): Ma 404, Ma 150. 3 Credits.

### Spring 2023 Course Information

- Instructor: Melissa Gardenghi
- Course Syllabus

## Additional Resources:

Discussion of dividing by n-1 for SD and stationarity of time series

Fully developed Linear Regression example using R

## Text-Related Resources:

Author's Textbook Site - text errata is available here

Free Text on Regression and ANOVA in R

Forecasting: Principles and Practices - free text using R

Little Book of R for Time Series

Matrix Differentiation - see Ch 5 (I think you will need to be on the campus network to access this) ... thanks to Stephen Sidwell for the resource

Inverse of Matrix of Matrices ... thanks to Dr. Brown for this resource

Proving : see pgs 8-10 of the D. Zeng's document and especially slides 31, 35-36, 44, 47-48, and 52-53 of K. Imai's slides.

Advanced Probability and Statistical Inference I - Donglin Zeng

## Additional Text:

An Introduction to Statistical Learning with Applications in R (see the SOA Exam SRM syllabus for a link to the full text)

Exam SRM: Statistics for Risk Modeling

Exam PA: Predictive Analytics

## Assignments/Projects:

The projects give students the opportunity to develop the following professional competencies:

### Resources for Using R/RStudio/RMarkdown

Here are some of the resources that I think might be most immediately helpful:

Base R for Exam PA Cheat Sheet - basic math/data stuff used in analytics

Advanced R Cheat Sheet - writing functions/using subsets

Data Visualization (ggplot2) Cheat Sheet - basic formatting of 2D and 3D plots

Plotly Cheat Sheet - dynamic graphing

Here's a link to additional R resources:

https://rstudio.com/resources/cheatsheets/

And don't forget the R Code that Frees has posted on the textbook website. You can see how he generated all of the output/plots that he used in the book (under the Statistical Software link).