Question

What is classification ? Explain inclusive and exclusive classification.

Answer 1

Answer:

Step-by-step explanation:

Exclusive Method– This method is used for those series in which the upper limit of one class becomes the lower limit of the next class. It is called as exclusive series because the frequencies of the upper limit of a class interval are not included in that particular class. In such type of series, the upper limit of one class becomes the lower limit of the next class, for example, 0–10, 10–20, 20–30 and so on. The upper limit is excluded but the lower limit is included in the class interval. This method is most appropriate for data of continuous variables.

Inclusive Method– Under this method of classification of data, the classes are formed in such a manner that the upper limit of a class interval does not repeat itself as the lower limit of the next class interval. In such a series, both the upper limit and the lower limit are included in the particular class interval, for example, 1–5, 6–10, 11–15 and so on. The interval 1–5 includes both the limits i.e. 1 and 5.

Answer 2

Classification is a process of categorizing items, individuals, or data into specific groups or classes based on certain characteristics or attributes. The goal of classification is to simplify the data and make it easier to understand and analyze.

There are two types of classification: inclusive and exclusive.

Inclusive classification involves grouping items together into broader categories, with the idea that each item belongs to one or more categories. For example, a fruit may be classified as a citrus fruit and also as a tropical fruit.

Exclusive classification, on the other hand, involves separating items into distinct categories, with the idea that each item belongs to only one category. For example, a fruit may be classified as either a citrus fruit or a tropical fruit, but not both.

Inclusive and exclusive classifications are used depending on the purpose of the classification and the goals of the analysis. Inclusive classification is often used when trying to understand patterns or relationships between multiple categories, while exclusive classification is used when trying to separate data into clear and distinct categories for further analysis.

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