With regard to grouping quantitative data into classes in which each class represents a range of possible values, there are two methods for depicting the classes. Identify the two methods and explain the relative advantages and disadvantages of each method. Identify the two methods and explain the relative advantages and disadvantages of each method. A. The methods are single-value grouping and cutpoint grouping. Both methods can be used when there are only a small number of distinct values. Single-value grouping is best used when the data are expressed as whole numbers, while cutpoint grouping is best used when the data are continuous and are expressed with decimals. B. The methods are single-value grouping and limit grouping. These methods can only be used when the data are discrete. Single-value grouping is best used when there are a small number of distinct values, while limit grouping is best used when there are a large number of distinct values. C. The methods are limit grouping and cutpoint grouping. Both methods can be used when there are too many distinct values to employ single-value grouping. Limit grouping is best used when the data are discrete and are expressed as whole numbers, while cutpoint grouping is best used when the data are continuous and are expressed with decimals. D. The methods are limit grouping and cutpoint grouping. Both methods can be used when there are too many distinct values to employ single-value grouping. Limit grouping is best used when the data are continuous and are expressed with decimals, while cutpoint grouping is best used when the data are discrete and are expressed as whole numbers.
With regard to grouping quantitative data into classes in which each class represents a range of possible values, there are two methods for depicting the classes. Identify the two methods and explain the relative advantages and disadvantages of each method. Identify the two methods and explain the relative advantages and disadvantages of each method. A. The methods are single-value grouping and cutpoint grouping. Both methods can be used when there are only a small number of distinct values. Single-value grouping is best used when the data are expressed as whole numbers, while cutpoint grouping is best used when the data are continuous and are expressed with decimals. B. The methods are single-value grouping and limit grouping. These methods can only be used when the data are discrete. Single-value grouping is best used when there are a small number of distinct values, while limit grouping is best used when there are a large number of distinct values. C. The methods are limit grouping and cutpoint grouping. Both methods can be used when there are too many distinct values to employ single-value grouping. Limit grouping is best used when the data are discrete and are expressed as whole numbers, while cutpoint grouping is best used when the data are continuous and are expressed with decimals. D. The methods are limit grouping and cutpoint grouping. Both methods can be used when there are too many distinct values to employ single-value grouping. Limit grouping is best used when the data are continuous and are expressed with decimals, while cutpoint grouping is best used when the data are discrete and are expressed as whole numbers.
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter12: Probability
Section12.4: Discrete Random Variables; Applications To Decision Making
Problem 25E
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With regard to grouping quantitative data into classes in which each class represents a range of possible values, there are two methods for depicting the classes. Identify the two methods and explain the relative advantages and disadvantages of each method.
Identify the two methods and explain the relative advantages and disadvantages of each method.
The methods are single-value grouping and cutpoint grouping. Both methods can be used when there are only a small number of distinct values. Single-value grouping is best used when the data are expressed as whole numbers, while cutpoint grouping is best used when the data are continuous and are expressed with decimals.
The methods are single-value grouping and limit grouping. These methods can only be used when the data are discrete. Single-value grouping is best used when there are a small number of distinct values, while limit grouping is best used when there are a large number of distinct values.
The methods are limit grouping and cutpoint grouping. Both methods can be used when there are too many distinct values to employ single-value grouping. Limit grouping is best used when the data are discrete and are expressed as whole numbers, while cutpoint grouping is best used when the data are continuous and are expressed with decimals.
The methods are limit grouping and cutpoint grouping. Both methods can be used when there are too many distinct values to employ single-value grouping. Limit grouping is best used when the data are continuous and are expressed with decimals, while cutpoint grouping is best used when the data are discrete and are expressed as whole numbers.
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