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A company’s management accountant is analysing the reject rates achieved by 100 factory operatives working in identical conditions. Reject rates, Y%, are found to be related to months of experience, X, by this regression equation: Y = 20 – 0.25X. (The correlation coefficient was r = -0.9.)
Using the equation, what is the predicted reject rate for an operative with 12 months’ experience?Solution.
Y=20-0,25x
x=12
%Y=20-(0.25*12)=17%
is x the number of 12 months?I really watched your lecture video and solved question additive model multiplicative model, but the questions are totally different:(:(
Regression and correlation coffecient, i solve it in both becker and bpp study text but when i come to bank test it is sth strange for me.
Could you explain the question please?
in this question how can i know x is 12?usually x means number of units .
y-total cost
a fixed cost
b variable cost per unit
x-number of unitsFirstly this has nothing to do with additive and multiplicative models – they are time series analysis but this question is regression analysis (it says so in the question)!
Secondly, regression analysis does not have to be based on numbers of units. It is an equation linking any two variables (and although the example in my lectures is units and costs, and most exam questions are, I do actually give examples of other things that could be linked together when I explain positive and negative correlation).
This question specifically says that reject rates are related to months of experience. Think about it. It makes sense – surely the more experience workers have then the less they are likely to make bad production and therefore have less rejects.
The question specifically says that X is the months of experience. So if they have 12 months experience then X must be equal to 12!
Probably, first time i opened and saw the question relating to forecasting and need eye adaptation.Thank you very much
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