Q.2.44 State three of the most importan... [FREE SOLUTION]

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Chapter 2: Q.2.44 (page 67)

State three of the most important guidelines in choosing the classes for grouping a quantitative data set.

Short Answer

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Three important guidelines to follow when selecting on classes for grouping quantitative data sets are:

Single-value grouping
Limit grouping.
Cut-point grouping.

Step by step solution

Concept Introduction

Quantitative variables: A variable that gives mathematical upsides of individual and Arithmetic activities.

Explanation

Grouping by one value: Quantitative data is organised into classes, each of which represents a single probable outcome.

Single-value classes are these kinds of classes, and single-value grouping is the way of grouping quantitative data.

Groupings should be limited. Class boundaries are a method of grouping quantitative data. Each class contains a number of different values.

The lower limit of the class is the smallest value that can be entered, while the upper limit of the class is the greatest number that may be entered. Limit grouping is a technique for categorising quantitative data.

Grouping by cut-points:To group quantitative data, utilise class cut-points, which consist of a range of values for each class. The lower cut-points of a class are the smallest values that could fit in the class, while the upper cut-points of the class are the smallest values that could fit in the next higher class.

Cut-points grouping is a way of categorising quantitative data using cut-points.