How Can You Effectively Explore Uncertainty in Time Series Analysis?

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Discussion Overview

The discussion centers around exploring uncertainty in time series analysis, particularly in the context of preparing for a presentation. Participants discuss various methods and models relevant to understanding and determining uncertainty in time series data.

Discussion Character

  • Exploratory
  • Technical explanation
  • Homework-related

Main Points Raised

  • One participant seeks guidance on how to effectively present uncertainty in time series analysis, expressing a lack of detailed knowledge on the topic.
  • Another participant suggests using ARIMA models as a classical approach to time series analysis, noting that uncertainty in these models can be calculated simply.
  • A participant questions whether the ARIMA approach is applicable to any time series data, reflecting on the assumption that knowledge of source uncertainties is sufficient for determining uncertainty in time series.
  • It is mentioned that while ARIMA can be applied to various data sources, its effectiveness is enhanced when the data exhibit autoregressive or moving average behavior. The variance prediction from ARIMA is highlighted as a means to determine uncertainty.
  • Another participant offers to assist further by inquiring about the original poster's engineering background.

Areas of Agreement / Disagreement

Participants have not reached a consensus on the applicability of ARIMA models to all time series data, and there are varying perspectives on the necessary knowledge for determining uncertainty.

Contextual Notes

There are limitations regarding the assumptions about data behavior and the specific requirements for applying ARIMA models, which remain unresolved in the discussion.

Who May Find This Useful

Individuals interested in time series analysis, particularly those preparing for presentations or seeking to understand uncertainty in data measurement and analysis.

piper28
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Hello all,

I am new to this forum and was wondering if any of you could help me out.

I have this interview scheduled for next week for which I have to prepare a 10 min presentation on Uncertainty and how to determine it in a time series. Now, there is a wealth of information of the net about uncertainty but nothing concrete when it comes to time series.

I am from an engineering background and have never studied uncertainty in any detail except for errors and measurement bias.
Also, this company is into measurement and data analysis and I am assuming these topics would be focussed towards measurement.

Could someone please point me in the right direction? does it have anything to do with correlation, standard uncertainty and linear regression analysis as I have been reading up on these for last couple of days.

Any help would be much appreciated.

Thanks.
 
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Thank you viraltux for your prompt response. Just wondering, would this approach apply to any time series data acquired from any source?

I think I was just naive enough to assume that only knowledge of the source uncertainties would be required to determine them in time series.
 
piper28 said:
Thank you viraltux for your prompt response. Just wondering, would this approach apply to any time series data acquired from any source?

I think I was just naive enough to assume that only knowledge of the source uncertainties would be required to determine them in time series.

You can apply it to any data regardless the source but, obviously, the ARIMA model becomes really useful if the data have an autoregressive / moving average behavior. Nonetheless, you can always use the variance prediction of the ARIMA model to determine the uncertainty of your time series.
 
Piper what is your engineering background. Maybe i could help you.
 

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