Q. The line which uses to join observations with lower and highest values of cost driver is called

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Q. A technique which minimizes sum of squared vertical difference, to determine the regression line is considered as

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Q. In Regression Analysis, if an observed cost value is 85 and the disturbance error is 25 then predicted cost value will be

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Q. The better fit between estimated cost and actual observations is represented by

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Q. If an unexplained variation is 456870 and the total variation is 955000, then the coefficient of determination will be

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Q. In Regression Analysis, the testing of assumptions if these are true or not is classified as

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Q. In estimation of cost functions, the variations in a single activity level represents the

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Q. An estimated coefficient, which indicates the degree by which the estimated values are affected by random factors is known as

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Q. The Regression Analysis Method of quantitative analysis of cost function considers

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Q. If the difference between costs linked to highest and lowest observation of cost driver is $36000 and observation of cost driver is 30 machine hours, then slope coefficient would be

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Q. In quantitative analysis of estimating cost function, the last and foremost step is to

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Q. The work measurement method of cost estimation is also called

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Q. The function which is used to measure the decline in per unit cost of different business functions is classified as

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Q. The worse fit between estimated cost and actual observations is shown on regression line with

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Q. The slope coefficient of linear cost function is

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Q. The learning curve models include

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Q. For slope coefficient b, the value of the estimated coefficient is considered as

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Q. If the difference between costs linked to highest and lowest observation of cost driver is $27000 and observation of cost driver is 90 machine hours, then slope coefficient would be

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Q. The cause and effect relationship between activity and costs is the result of

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Q. If the difference in costs is $9000 and the difference in machine hours is $15000, then slope coefficient would be

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