Time Series Analysis in Excel | Forecasting & Data Science

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This Time Series Analysis (Part-1) tutorial will help you understand what is time series, why time series, components of time series, when not to use time series, why does a time series have to be stationary, how to make a time series stationary and at the end, you will also see a use case where we will forecast car sales for 5th year using the given data.

Link to Time Series Analysis Part-2: https://www.youtube.com/watch?v=Y5T3ZEMZZKs

You can also go through the slides here: https://goo.gl/RsAEB8

A time series is a sequence of data being recorded at specific time intervals. The past values are analyzed to forecast a future which is time-dependent. Compared to other forecast algorithms, with time series we deal with a single variable which is dependent on time. So, lets deep dive into this video and understand what is time series and how to implement time series using R.

Below topics are explained in this Time Series in R Tutorial -

1. Why time series?
2. What is time series?
3. Components of a time series
4. When not to use time series?
5. Why does a time series have to be stationary?
6. How to make a time series stationary?
7. Example: Forecast car sales for the 5th year

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