To determine which statement about Euclidean distance is not true, let’s analyze each option step-by-step:
1. Euclidean distance requires at least one variable that measures spatiality.
- Euclidean distance is a measure of the straight-line distance between two points in any space. It does not specifically require the variables to measure spatiality, meaning it can be applied to numeric data regardless of whether it represents physical space or not. Therefore, this statement is not true.
2. Euclidean distance is the straight-line distance between two points.
- This is the definition of Euclidean distance. It is computed as the straight-line or direct distance between two points in a multidimensional space. Therefore, this statement is true.
3. Euclidean distance includes geographic and non-geographic distance calculations.
- Euclidean distance is versatile and can be applied to various forms of numeric data including both geographic (physical space) and non-geographic contexts (such as feature space in data science). Thus, this statement is true.
4. Euclidean distance is the sum of squared differences in the distance measures between two data points.
- The Euclidean distance is actually calculated as the square root of the sum of squared differences in the distance measures between two data points. So, stating it is just the sum of squared differences is inaccurate. Thus, this statement is not true.
Given the analysis:
- The first statement is not true.
- The second statement is true.
- The third statement is true.
- The fourth statement is not true.
Hence, the first option that is not true is the first statement. Therefore, the correct answer is the first option.
