Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
Random and Systematic Errors01:20

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
Random and Systematic Errors01:20

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
Common Leveling Mistakes and Errors01:17

Common Leveling Mistakes and Errors

A survey team is tasked with determining the elevation difference between points Point A and Point B, separated by uneven terrain. They use a leveling instrument and a leveling rod.Common MistakesMisreading the Rod: During a backsight reading at Point A, the instrumentman observes the rod partially obscured by tall grass. Instead of reading 1.135 m, they mistakenly record 1.735 m due to the misalignment of the crosshair with the wrong graduation. This error adds 0.600 m to all subsequent...
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Preoperative prognostic prediction for invasive pulmonary adenocarcinoma: Impact of <sup>18</sup>F-FDG PET/CT semi-quantitative parameters associated with new histological subtype classification.

Clinical radiology·2024
Same author

Single-composition Al<sup>3+</sup>-singly doped ZnO phosphors for UV-pumped warm white light-emitting diode applications.

Dalton transactions (Cambridge, England : 2003)·2021
Same author

Target antifungal peptides of immune signalling pathways in silkworm, Bombyx mori, against Beauveria bassiana.

Insect molecular biology·2020
Same author

Whole-body magnetic resonance imaging is superior to skeletal scintigraphy for the detection of bone metastatic tumors: a meta-analysis.

European review for medical and pharmacological sciences·2020
Same author

<i>Reply</i>.

AJNR. American journal of neuroradiology·2019
Same author

Treatment Response Prediction of Nasopharyngeal Carcinoma Based on Histogram Analysis of Diffusional Kurtosis Imaging.

AJNR. American journal of neuroradiology·2019

Related Experiment Video

Updated: Jul 7, 2026

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals
07:34

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Published on: August 22, 2019

Sources of systematic errors in line intensities.

J H Shaw1, N Tu, D L Agresta

  • 1Ohio State University, Physics Department, Columbus, Ohio 43210, USA.

Applied Optics
|August 1, 1985
PubMed
Summary

Accurate spectral line intensity measurements require precise linewidth and spectral resolution values. Incorrect assumptions lead to systematic errors in line intensity analysis, impacting astrophysical and atmospheric studies.

Area of Science:

  • Spectroscopy
  • Astrophysics
  • Atmospheric Science

Background:

  • Line intensities are crucial for quantitative analysis in spectroscopy.
  • The curve of growth method relates line intensity to physical conditions.
  • Accurate determination of spectral parameters is essential for reliable results.

Purpose of the Study:

  • To investigate the impact of assumed linewidth and spectral resolution on line intensity measurements.
  • To demonstrate the systematic errors introduced by incorrect spectral parameters.

Main Methods:

  • Analysis of simulated weak Lorentz-shaped spectral lines.
  • Evaluation of line intensities under varying linewidth and spectral resolution assumptions.

Main Results:

More Related Videos

X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells
10:16

X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells

Published on: August 20, 2019

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
10:22

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements

Published on: September 7, 2019

Related Experiment Videos

Last Updated: Jul 7, 2026

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals
07:34

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Published on: August 22, 2019

X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells
10:16

X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells

Published on: August 20, 2019

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
10:22

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements

Published on: September 7, 2019

  • Line intensities are sensitive to assumed linewidth and spectral resolution.
  • Deviations from true values introduce systematic errors in calculated line intensities.
  • The linear region of the curve of growth is particularly affected.

Conclusions:

  • Precise knowledge of linewidth and spectral resolution is critical for accurate line intensity determination.
  • Incorrect spectral parameters lead to unreliable quantitative spectroscopic analysis.
  • Careful consideration of instrumental and line profile effects is necessary.