ARIMA Forecasting in R Part 1 - Exploratory Data Analysis

This is part one of a six part video series on how to do an accurate ARIMA forecast in R. this is a complete walk-through of a data science and/or data analysis project. In this video I walk you through every bit of the exploratory data analysis we are going to do.

We start by loading in the correct libraries. Next we start the exploratory data analysis by making sure that our date column is in the correct format and date class. Then we graph our data and look at it for the variance and outliers and then we clean the data. This is an important first step because if the data is messy and unclean you will be left with a very unreliable forecast in the end.

Get a free stock like Apple, Ford, or Facebook worth up to $500 just by signing up and joining Robinhood using my link: https://join.robinhood.com/davidm16707

Make sure you are looking at a time series data set which means data for a range of dates and it has to be in a series - which means daily or weekly or monthly. Daily is the preferred because we can always go to weekly or monthly from that. It's hard to go backwards if you're starting with weekly or monthly data.

In this video I show you also how to document your project and results for your requesters, management and executives and anyone else you want to see it. The graphs in visuals that we create throughout this entire video series will help you to document all the testing and accuracy behind your and forecasting product. So do not take any of these pieces lightly.

Again this is part one of a six part video series. Please be sure and watch all the other five parts you know how to do this process of creating a highly accurate Arima model in R.

I hope you found this both informational and entertaining.

Please be sure and subscribe and like so you can see all my other great videos and be notified when I publish new ones.

Thanks again and God bless!