Introduction to Time Series Analysis

A step-by-step guide on how to build an ARIMA model for sales forecasting. Work on a real-life example on how to accurately predict sales for a retail electronics store.
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Introduction to Time Series Analysis

Access: Subscribers only

Time series modeling has a wide range of business applications.

Hotels use their historic booking data to predict the booking rate for the upcoming holiday season.

Retailers analyze the seasonal trend and forecast their sales for inventory management.

In this project, we will analyze the 60-day average daily demand at a physical retail store.

By the end of the project, you will have learned, step-by-step, how to build a time series model that can be used for sales forecasting.

This course is based on SAS OnDemand for Academics, which is free to download.

Important! This is a coding-oriented course. You must set up the training page as instructed below:

This course is for those who want to learn how to perform a real-life sales prediction analysis using an ARIMA model.

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