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Overview of Microsoft Excel as a Data Analysis Tool01:13

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In Microsoft Excel, plotting the mean along with standard deviation (SD) and standard error (SE) helps visualize data variability and reliability. To plot these values, follow these steps:
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Simple and Quick Visualization of Periodical Data Using Microsoft Excel.

Hideaki Oike1,2, Yukino Ogawa3, Katsutaka Oishi4,5,6,7

  • 1Food Research Institute, National Agriculture and Food Research Organization (NARO), Tsukuba, Ibaraki 305-8642, Japan. oike@affrc.go.jp.

Methods and Protocols
|October 17, 2019
PubMed
Summary
This summary is machine-generated.

This study presents a simple Microsoft Excel method for creating actograms, which visualize biological rhythms. This user-friendly approach benefits students and researchers by simplifying the analysis of time-series data.

Keywords:
ECGEEGactogrambiological rhythmchronobiologycircadian clockheatmapsleep pattern

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Area of Science:

  • Chronobiology
  • Data Visualization
  • Scientific Research Methods

Background:

  • Actograms are crucial for visualizing periodic activity in chronobiological research.
  • Existing specialized software can be inconvenient for new users, including students and researchers from diverse fields.
  • Understanding biological rhythms is essential for various scientific disciplines.

Purpose of the Study:

  • To demonstrate a fast and user-friendly method for creating actograms using Microsoft Excel.
  • To provide a simplified tool for visualizing time-series data and understanding periodic phenomena.
  • To make actogram creation accessible to a broader audience, including students and non-specialists.

Main Methods:

  • Utilizing Microsoft Excel's simple and intuitive operations to generate actograms.
  • Applying the method to various time-series data, including activity, body temperature, and gene expression.
  • Converting standard actograms into "heatograms" for enhanced visual interpretation.

Main Results:

  • Actograms can be created in minutes using the proposed Excel method.
  • The method allows visualization of rhythmic characteristics from diverse time-series data.
  • The "heatogram" conversion offers a more intuitive understanding of rhythmic features.

Conclusions:

  • The Microsoft Excel method offers a convenient and beneficial approach to creating actograms.
  • This technique aids in the better understanding of periodic phenomena from large datasets.
  • It empowers a wider range of researchers, especially students, to analyze biological rhythms effectively.