Interval Data
Interval data is a type of quantitative data that is measured on a scale with equal intervals between each value. This means that the difference between any two values is the same throughout the scale. Interval data is commonly used in data science for statistical analysis and machine learning algorithms. Examples of interval data include temperature measurements in Celsius or Fahrenheit, time measurements in hours or minutes, and IQ scores. Interval data is often analyzed using descriptive statistics such as mean, standard deviation, and correlation coefficients. In machine learning, interval data is often preprocessed using techniques such as normalization or standardization to ensure that the data is on the same scale and to improve the performance of the algorithms.
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