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The correct distinction between continuous and categorical data lies in their characteristics. Continuous data can take on an infinite number of values within a given range (such as height, weight, temperature) and is typically represented by numeric values. It can be measured and expressed with high precision. In contrast, categorical data is non-numeric and represents distinct categories or groups (such as gender, color, or product type). These categories can be nominal (no specific order, like color) or ordinal (with a defined order, like education level), but the defining trait is that they do not have the same range of values as continuous data. Option A (Continuous data is always numeric, while categorical data is always non-numeric) is partially true, but not all continuous data is numeric (e.g., continuous time data could be expressed in non-numeric units). Option B (Continuous data represents distinct groups, while categorical data represents measurable quantities) is incorrect because continuous data represents measurable quantities, not groups. Option D (Categorical data can only be ordinal, while continuous data is always nominal) is incorrect because categorical data can be both ordinal and nominal, while continuous data cannot be either. Option E (Continuous data is qualitative, while categorical data is quantitative) is incorrect because continuous data is quantitative, not qualitative.
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