Q. In estimation of cost function, an example of independent variable is

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Q. In regression analysis, if an observed cost value is 65 and the disturbance error is 32 then predicted cost value will be

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Q. The formula of 1 - unexplained variation ⁄ total variation is used to calculate

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Q. The cause and effect relationship that exists between change in total cost level and change in level of activity, is measured with the help of

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Q. The cost that has elements of variable and fixed costs at the same time is

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Q. If an unexplained variation is 255050 and the total variation is 550505, then coefficient of determination will be

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Q. If the difference in costs is $32000 and the slope coefficient is 0.40, then difference in machine hours would be

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Q. In plotting of cost functions, the level of activities according to which the charged cost is represented on

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Q. The function used to measure decline in labor hours per unit as the units of production increases is called

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Q. If the difference in costs is $16000 and the slope coefficient is 0.40, then difference in machine hours would be

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Q. In the linear cost function, which is y = a + bx, the 'y' is classified as

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Q. In the specification analysis, the assumptions related to linearity states but linearity must be within

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Q. In regression analysis, if the predicted cost value is 65 and observed cost value is 19 then the disturbance term will be

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Q. In adjustment issues of costing, the database must consider wide range values of

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Q. The method, which considers the cost and cost drivers of departments such as employee relations and process engineering is termed as

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Q. The examples of nonlinear cost functions are

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Q. If the residual error is 35 and the predicted cost value is 20, then the observed cost value will be

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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 relationship between cost and cost driver is economically plausible if the goodness of fit

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Q. The situation in which two or more independent variables are highly correlated is known as

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