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For the past year a manufacturing company has recorded the number of units produced (x) each week and the total production cost (y) for that week. The company intends to use this data to predict future costs.
For the circumstance described above, linear regression is more useful and accurate than the high-low method because:
1. It uses all the sets of data observed to calculate the line of best fit.
2. The coefficient of variation can estimate what percentage of x is due to a change in y.
3. Forecasts remain valid for values for x outside of the observed range.
Which of the above statements are true?
The standard production cost of making a product is as follows:

What is the fixed production overhead efficiency variance?
Give your answer as a whole number.
The standard output from a joint process is 4,000 litres of Product K, 6,000 litres of Product L and 3,000 litres of Product M.
The total cost of the joint process is $147,000.
The company is now deciding if it should further process Product L.
In the further processing decision the best way to apportion the joint costs to the products is:
TP makes wedding cakes that are sold to specialist retail outlets which decorate the cakes according to the customers’ specific requirements. The standard cost per unit of its most popular cake is as follows:

The general market prices at the time of purchase for Ingredient A and Ingredient B were $23 per kg and $20 per kg respectively. TP operates a JIT purchasing system for ingredients and a JIT production system; therefore, there was no inventory during the period.
Discuss the usefulness of the planning and operational variances calculated for TP’s management.
Select ALL the TRUE statements.
Place the type of budget or cost against its definition.

The inventory level of Product Y has reduced by 40 units over a single period. The cost card for Product Y is as follows:

The profit for Product Y using marginal costing is $26,000.
If the company used absorption costing, what would the profit for Product Y be?
Give your answer to the nearest whole $.
The maximum availability of a material is 8,000 kg.
Product A requires 5 kg of this material and Product B requires 7 kg of this material which is in short supply.
The correct constraint to include for the material when formulating the linear programming problem is:
A company produces a product that requires two materials, Material A and Material B. Details of the material quantities and costs for August are given in the table below.

Budgeted and actual output of the product for August was 12,000 units.
The material yield variance for August is:
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