Q. A technique for estimating regression line, which minimizes the sum of vertical deviations squares is classified as

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Q. The type of relationship stating "how changes in cost driver drives cause changes in cost" will be termed as

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Q. The slope coefficient of cost function is zero because it intersects the

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Q. An assumption of specification analysis, which states all the values of residuals which are uniformly scattered around regression line is classified as

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Q. The goodness of fit is used to measure the wellness of

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Q. The slope coefficient is 0.75 and the difference in machine hours is $65000, then difference in cost would be

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Q. In regression equation, an evaluation criteria considers the significance of

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Q. The high-low method is used for estimation of

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Q. All the conditions or assumptions of regression analysis in simple regression can give

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Q. Industrial engineering method is used to analyze the relationship between

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Q. The residual term is also considered as

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Q. The percentage of variation in the 'Y' explained by the 'X' is measured by

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Q. The small residual terms and positive slope of line indicate

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Q. An analysis of data over successive past periods, which pertain to some plant, activity and organization is called

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Q. The individual variable coefficient's multicollinearity leads to

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Q. The constant variance is classified in assumptions testing as

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Q. As compared to cumulative average-time learning model, the learning model which predicts more cumulative total time to produce more units is known as

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Q. The model, in which the produced unit doubles every time as the cumulative average time per unit decreases, by a constant percentage can be classified as

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Q. In the specification analysis, the assumptions related to variance state that:

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Q. If the slope coefficient is 0.60 and the difference in machine hours is $50000, then difference in cost can be

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