High Low Method: In this method, the highest level and the lowest level of activity is taken and comparing the total cost at each level. If variable cost charged at same level and fixed cost remain same then, it is possible to identify the fixed and variable cost. Least square regression method: It is a statistical procedure which was using to find the best fit for a set of data points by minimizing the sum of the from the plotted curve. To find out: The reasons for differences between cost prediction on the high low method and least square method.

Question

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Answer 1

Question

Chapter 5, Problem 3.3GBP

To determine

Concept introduction:

High Low Method: In this method, the highest level and the lowest level of activity is taken and comparing the total cost at each level. If variable cost charged at same level and fixed cost remain same then, it is possible to identify the fixed and variable cost.

Least square regression method: It is a statistical procedure which was using to find the best fit for a set of data points by minimizing the sum of the from the plotted curve.

To find out:

The reasons for differences between cost prediction on the high low method and least square method.

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Answer 2

Question

Chapter 5, Problem 3.3GBP

To determine

Concept introduction:

High Low Method: In this method, the highest level and the lowest level of activity is taken and comparing the total cost at each level. If variable cost charged at same level and fixed cost remain same then, it is possible to identify the fixed and variable cost.

Least square regression method: It is a statistical procedure which was using to find the best fit for a set of data points by minimizing the sum of the from the plotted curve.

To find out:

The reasons for differences between cost prediction on the high low method and least square method.

Expert Solution & Answer

Want to see the full answer?

Check out a sample textbook solution

See solution

Answer 3

Question

Chapter 5, Problem 3.3GBP

To determine

Concept introduction:

High Low Method: In this method, the highest level and the lowest level of activity is taken and comparing the total cost at each level. If variable cost charged at same level and fixed cost remain same then, it is possible to identify the fixed and variable cost.

Least square regression method: It is a statistical procedure which was using to find the best fit for a set of data points by minimizing the sum of the from the plotted curve.

To find out:

The reasons for differences between cost prediction on the high low method and least square method.

Expert Solution & Answer

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Check out a sample textbook solution

See solution

Answer 4

Question

Chapter 5, Problem 3.3GBP

To determine

Concept introduction:

High Low Method: In this method, the highest level and the lowest level of activity is taken and comparing the total cost at each level. If variable cost charged at same level and fixed cost remain same then, it is possible to identify the fixed and variable cost.

Least square regression method: It is a statistical procedure which was using to find the best fit for a set of data points by minimizing the sum of the from the plotted curve.

To find out:

The reasons for differences between cost prediction on the high low method and least square method.

Expert Solution & Answer

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Check out a sample textbook solution

See solution

Answer 5

Chapter 5, Problem 3.3GBP

To determine

Concept introduction:

High Low Method: In this method, the highest level and the lowest level of activity is taken and comparing the total cost at each level. If variable cost charged at same level and fixed cost remain same then, it is possible to identify the fixed and variable cost.

Least square regression method: It is a statistical procedure which was using to find the best fit for a set of data points by minimizing the sum of the from the plotted curve.

To find out:

The reasons for differences between cost prediction on the high low method and least square method.

Answer 6

Chapter 5, Problem 3.3GBP

To determine

Concept introduction:

High Low Method: In this method, the highest level and the lowest level of activity is taken and comparing the total cost at each level. If variable cost charged at same level and fixed cost remain same then, it is possible to identify the fixed and variable cost.

Least square regression method: It is a statistical procedure which was using to find the best fit for a set of data points by minimizing the sum of the from the plotted curve.

To find out:

The reasons for differences between cost prediction on the high low method and least square method.

Answer 7

Chapter 5, Problem 3.3GBP

To determine

Concept introduction:

High Low Method: In this method, the highest level and the lowest level of activity is taken and comparing the total cost at each level. If variable cost charged at same level and fixed cost remain same then, it is possible to identify the fixed and variable cost.

Least square regression method: It is a statistical procedure which was using to find the best fit for a set of data points by minimizing the sum of the from the plotted curve.

To find out:

The reasons for differences between cost prediction on the high low method and least square method.

Answer 8

Expert Solution & Answer

Answer 9

Expert Solution & Answer

Answer 10

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Answer 11

Ch. 5 - Define each of the following terms variable cost,...Ch. 5 - Prob. 2Q Ch. 5 - Prob. 3Q Ch. 5 - Prob. 4Q Ch. 5 - Prob. 5Q Ch. 5 - Describe the three methods used to estimate cost...Ch. 5 - Prob. 7Q Ch. 5 - Prob. 8Q Ch. 5 - Prob. 9Q Ch. 5 - Prob. 10Q

Solution Summary: The author explains the differences between the high-low and least-square regression methods. Scatter chart and low-cost method do not consider full data for computation. Regression analysis is more accurate and effective.

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