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In the original conception of the Likert scale, this value representation was just a number. Lower numbers indicated negative attitudes and higher numbers indicated positive attitudes. However, this value need not be a number.
A Likert scale is technically ordinal but there is consistent support for the use of these variables as approximately continuous. Therefore, it can be considered as both categorical (named/nominal) and continuous .
The general consensus from these studies is that fully labeled scales produce better data quality than partially labeled scales. Krosnick and Fabrigar (1997) came to this conclusion based on a review of several studies that examined the reliability and validity of fully versus partially labeled scales.
The Likert 5-point scale was employed to evaluate the variables, reflecting the extent of performance from low to high. This scale has five ranges: 1-1.80 for strongly disagree, 1.81-2.60 for disagree, 2.61-3.40 for neutral, 3.41-4.20 for agree, and 4.21-5 for strongly agree [26] .
A typical Likert scale item has 5 to 11 points that indicate the degree of something. For example, it could measure agreement with a statement, such as 1=Strongly Disagree to 5=Strongly Agree. It can be a 1 to 5 scale, 0 to 10, etc.

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When using Likert scale questions, the analysis tools used are mean, median, and mode. These help better understand the information collected. The mean (or average) is the average value of data, calculated by adding all the numbers and dividing this sum by the total number of values offered to respondents.
How to analyse data from scale questions Averaging. The most basic method of analysing scale question data is simply averaging the ratings given to each item like the example below. Scoring responses. Top box comparison. Respondent level rank scoring. Primacy share. Standardize scoring.
A numeric rating scale question asks survey participants to measure preferences, feelings, perceptions, and interests on a provided numerical scale. The scale is an ordered-number scale with a range determined by the researcher to represent the extremes of the value being measured.