Module 10: Averaging and Data Inspection

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Module 10 Overview:

This module introduces the averaging of trials into conditions for individual data sets and then combining data sets into a grand average. It shows how averaging reduces noise to reveal the underlying signal. It also shows students how to examine data quality in the individual averaged data sets.

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Module Navigation

Module 1: Overview of EEG/ERP

Module 2: Source of the EEG Waveform

Module 3: ERP Components

Module 4: ERPs in Research

Module 5: Experimental Design

Module 6: Programming Experiments

Module 7: Recording

Module 8: Ethics

Module 9: Data Preprocessing

Module 10: Averaging & Data Inspection

Module 11: Data Quantification & Statistics

Module 12: Data Visualization & Communication

Module 13: Final Project & Assessment

Instructor Support Materials

Unit:

Averaging and Data Inspection

Learning Goals:

  • Explain the reasons why we average EEG/ERP data
  • Describe how artifact noise affects averages
  • Recognize the difference between averaging within participants across trials and averaging across participants.
  • Grand Averaging and discuss issues and evaluate problems in grand averages.

Materials Included: Slides, In-class Activities, In-class Lab, Take-home Lab

Averaging and Data Inspection Lab: In this lab students will learn to create individual data set averages, inspect individual averages for data quality, and to create grand averages.