A significant weakness of the ordinal scale is the lack of precise measurement and equal intervals between categories. In an ordinal scale,datais ranked or ordered based on a particular characteristic or attribute, but the numerical distance or magnitude between the categories is not defined or consistent. This makes it difficult to make precise comparisons or perform mathematical operations on the data.Unlike interval or ratio scales, where the intervals between values are equal and the data can be subjected to meaningful mathematical calculations,ordinalscales only provide information about the relative order or rank of the data points. The scale does not convey information about the magnitude of the differences between the categories or allow for accurate measurement of the distance between them.For example, if we have an ordinal scale ranking customer satisfaction as "high," "medium," and "low," we know the order of satisfaction levels but not the exact difference between "high" and "medium" or "medium" and "low." This lack of precisemeasurementlimits the statistical analysis and interpretation of data collected using an ordinal scale.Therefore, while the ordinal scale provides an ordered representation of data, it is less informative in terms of quantitativeanalysisand does not allow for precise comparisons or calculations.To know more thandata,visitbrainly.com/question/29961082#SPJ11...

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