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Related Concept Videos

How Data are Classified: Numerical Data00:59

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Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
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A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
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While the differential rate law relates the rate and concentrations of reactants, a second form of rate law called the integrated rate law relates concentrations of reactants and time. Integrated rate laws can be used to determine the amount of reactant or product present after a period of time or to estimate the time required for a reaction to proceed to a certain extent. For example, an integrated rate law helps determine the length of time a radioactive material must be stored for its...
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Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
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Consider a real-valued function defined on a closed interval. One of the fundamental objectives in calculus is to determine the area under the graph of such a function. When an exact computation is not readily available, this area can be estimated by dividing the interval into a finite number of equal subintervals. Each subinterval corresponds to a rectangle whose width is the length of the subinterval and whose height is determined by the value of the function at a selected point within that...
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Exploring, Mapping, and Data Management Integration of Habitable Environments in Astrobiology.

Marjorie A Chan1, Brenda B Bowen1, Frank A Corsetti2

  • 1Department of Geology and Geophysics, The University of Utah, Salt Lake City, UT, United States.

Frontiers in Microbiology
|March 21, 2019
PubMed
Summary

Authigenic minerals on Mars offer promising sites for preserving biosignatures. Integrating diverse data scales with GIS can pinpoint habitable "sweet spots" for astrobiology exploration.

Keywords:
Marsastrobiologyauthigenic mineralscybertechnologydata managementhabitable environments

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Area of Science:

  • Astrobiology
  • Geoscience
  • Planetary Science
  • Microbiology
  • Geoinformatics

Background:

  • Authigenic minerals are abundant on Mars and Earth, preserving microbial life and biosignatures.
  • Astrobiology research faces challenges due to scale mismatches between macro (satellite) and micro (microbial) observations.
  • Identifying habitable environments is key to searching for extraterrestrial life.

Purpose of the Study:

  • To propose an integrated, multi-scale approach for astrobiology exploration.
  • To address the scale mismatch in astrobiological data analysis.
  • To leverage geoinformatics and cyberinfrastructure for enhanced discovery.

Main Methods:

  • Blending geoscience, planetary science, microbiology, geoinformatics, and cyberinfrastructure.
  • Quantifying geospatial and temporal/spatial relationships of microbial life within authigenic minerals.
  • Utilizing statistical measures, computer vision, and Geographic Information Systems (GIS).

Main Results:

  • Authigenic minerals are crucial for preserving biosignatures.
  • An integrated, multi-scale approach can overcome data limitations.
  • GIS and data-driven methods can predict habitable environments.

Conclusions:

  • An "Astrobiology Information System" integrating diverse data scales is essential.
  • This system will guide researchers to "sweet spots" of habitability.
  • The approach enhances the search for evidence of life in the solar system and beyond.