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Related Concept Videos

Ordinal Level of Measurement00:55

Ordinal Level of Measurement

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The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
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Ratio Level of Measurement00:54

Ratio Level of Measurement

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The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
A set of data measured using the ratio scale takes care of the ratio problem and provides complete information. Ratio scale data are like interval scale data, except they have a zero point and ratios can be calculated....
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Interval Level of Measurement00:55

Interval Level of Measurement

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For effective statistical analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using the interval scale are similar to ordinal level data because they have a definite arrangement. However, in the interval level of measurement, the differences between data values are meaningful even though the data does not have a starting point.
Temperature is measured using the interval scale. It is measurable data, and the difference between...
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Review and Preview01:10

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In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
Percentiles are a type of fractile that partition data into...
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Nominal Level of Measurement00:56

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The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. Not every statistical operation can be used with every set of data. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
The data that cannot be measured but can be grouped into categories fall under the nominal level of measurement. Data that is measured using a nominal...
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Design Example: Measuring Distance Between Two Points with Obstructions01:10

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When measuring distances in areas with physical obstructions, such as a lake in a field, surveyors must employ techniques to calculate accurate lengths without direct line measurements. One effective method is the offset technique, which allows for precise distance estimation over inaccessible stretches.In this scenario, a surveyor must measure a side of an area that crosses a lake. Since the measuring tape cannot span the lake, the surveyor begins by establishing a baseline that aligns with...
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Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
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Measuring User Experience With 3, 5, 7, or 11 Points : Does It Matter?

James R Lewis1

  • 1525817 IBM Corp., Delray Beach, Florida, USA.

Human Factors
|October 12, 2019
PubMed
Summary

The number of response options on the Usability Metric for User Experience Lite (UMUX-LITE) questionnaire generally does not impact results significantly. However, avoid the three-response option version due to reliability concerns.

Keywords:
UXlikelihood-to-recommendperceived usabilityresponse optionsstandardized usability questionnaires

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Area of Science:

  • Human-Computer Interaction
  • Usability Engineering
  • Psychometrics

Background:

  • The Usability Metric for User Experience Lite (UMUX-LITE) is a brief, validated questionnaire for assessing perceived usability.
  • UMUX-LITE demonstrates strong correlations with the System Usability Scale (SUS), a widely adopted usability measure.
  • While the standard UMUX-LITE uses seven response options, variations with three, five, and eleven options exist in practice.

Purpose of the Study:

  • To evaluate the impact of varying response option counts (3, 5, 7, 11) on the UMUX-LITE questionnaire's psychometric properties and validity.
  • To determine if different UMUX-LITE versions yield comparable results to the standard seven-option version and the SUS.
  • To provide evidence-based recommendations for selecting the most appropriate UMUX-LITE version for usability research.

Main Methods:

  • A corporate user experience panel (n=242) evaluated a website using both the SUS and UMUX-LITE with different response scales.
  • Participants also provided ratings for overall user experience and likelihood to recommend the website.
  • Statistical analyses examined scale reliability (Cronbach's alpha) and correlations between UMUX-LITE, SUS, overall experience, and likelihood-to-recommend.

Main Results:

  • All UMUX-LITE versions, except the three-response option scale, exhibited acceptable reliability (α >.70).
  • All UMUX-LITE versions showed significant correlations with the SUS, overall experience, and likelihood-to-recommend.
  • The eleven-response option version demonstrated a stronger correlation with likelihood-to-recommend compared to the three-response option version.

Conclusions:

  • The number of response options for UMUX-LITE has minimal practical impact on usability assessment outcomes.
  • The three-response option version should be avoided due to lower reliability and weaker correlation with likelihood-to-recommend.
  • The standard seven-response option UMUX-LITE is recommended for general use unless specific research needs dictate otherwise.