Boxcar Average: A Simple and Lousy Filtering Mechanism?

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SUMMARY

The Boxcar Average is a mathematical function utilized in various programming languages and as a setting in lock-in amplifiers. It operates by averaging the last n data points from a 1D array, effectively smoothing out anomalies in the data. While it serves as a basic filtering mechanism, it is often criticized for its simplicity and ineffectiveness in handling complex data sets.

PREREQUISITES
  • Understanding of basic statistical concepts, particularly averaging.
  • Familiarity with 1D arrays in programming languages.
  • Knowledge of lock-in amplifiers and their settings.
  • Experience with data filtering techniques.
NEXT STEPS
  • Research advanced filtering techniques such as Kalman filters.
  • Learn about moving averages and their applications in data analysis.
  • Explore the implementation of Boxcar Average in Python or MATLAB.
  • Investigate the limitations of Boxcar Average in real-world data scenarios.
USEFUL FOR

Data analysts, engineers working with signal processing, and anyone interested in basic data smoothing techniques.

flatmaster
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What is a "Boxcar Average"?

Hi, I'm Brand new to the Forums. I'm not sure this is the right forum. This may belong more under "experimental techniques" What is a "Boxcar Average"? I've seen it as both a mathematical function in some languages, and as a setting on my lock-in Amplifier. I think it may automatically throw out data points that are extremely far from your other data values.
 
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Think I figured it out. It takes a 1D array of data and averages the last n data points to level out any weird data. Is this right?
 


Yes. It's a rather simple and rather lousy filtering mechanism.
 

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