The right time Group Breakdown is that 1 800 | Time frame Number in R | Valuable time Combination of In preparation | Records Research | Simplilearn

This Time Series Analysis (Part-1) in R 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: Forcast car sales for the 5th year

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Video Rating: / 5

What is the difference between Confidence Intervals and Prediction Intervals? And how do you calculate and plot them in your graphs?
Video Rating: / 5

30 Gedanken zu „The right time Group Breakdown is that 1 800 | Time frame Number in R | Valuable time Combination of In preparation | Records Research | Simplilearn“

  1. Do you have any questions on this topic? Please share your feedback in the comment section below and we'll have our experts answer it for you.

    Thanks for watching the video. Cheers!

  2. Stationary data graph looks like a sign function graph – But you mentioned, it doesn't make sense to apply TS forecasting on a sin function like data. Then why do you want to make the data stationary?

  3. Thank you for the video. Can you please explain how you got the values of St? The average of first quarter can't give us 0.90. Thank you

  4. Dr. Verschuuren – I have the same question as "Henryluyu" below. All discussions I have seen about 95% Confidence Interval and 95% Prediction Interval are in the context of a linear relation of the form Y = aX + b. What if I have a quadratic relation Y = aX^2 + bX + c? To me philosophically, the entities "95% C.I." and "95% P.I." should exist irrespective of the relation between the dependent and independent variable. I can understand that when there are multiple variables, it can get much more challenging. For now, if I am looking at a single independent variable but a quadratic relation, I am at a loss to figure out how to calculate 95% C.I. and 95% P.I. Could you please guide me? Also, I am looking for techniques using just Excel. Thank you.

  5. Dr. Verschuuren,

    Thanks for sharing this great video. I spent hours on Google trying to find this very thing for one of my graduate classes. Everything I read covered the principals and theory behind this, which is great, I need to know that too. But failed to cover how to make the Excel charts.

    Erg bedankt,
    Jeff

  6. Many thanks. The case shown here is about the linear fitting. I am wondering if this method is applicable to nonlinear fitting. If not, how to calculate the confidence and prediction intervals for nonlinear fitting?
    Best wishes.

  7. Dear Dr Gerard

    Thank you very much for sharing this Video but I am wondering how predication and confidence interval both can be done for a power regression curve instead of linear regression line. Will it be possible to show any power regression curve or tell us what should we change in the equations to get it done.

    Thank you again and looking forward to hear from you regarding this issue.

    BR

    Fahad khshim

  8. Hello Dr. Gerard!
    So great videos, thank for sharing them!
    Just by chance… do yo know what function has to be used when I have more than 30 samples? 
    I did a previous search and I think that the z-test has to be applied, but I don't know what excel function to use. Thanks!

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