Discuss and provide Detailed Explanations and references to the following questions. Answer only if you are SURE.

(a) Explain the advantages and disadvantages of the high-low method of cost estimation. (b)Central Machinery Ltd. is preparing its budget for the year ending 30 June 2004. For the fuel expenses consumption it is decided to estimate an equation of the form, y = a + bx, where y is the total expense at an activity level x, a is the fixed expense and b is the rate of variable cost. The following information relate to the year ended 30 June 2003: Month Machine Fuel Oil Month Machine Fuel oil hours expense hours expense 2003 (Sh. '000') (Sh. '000') 2004 (Sh. (Sh. '000') '000') July 34 640 January 26 500 August 30 620 February 26 500 September 34 620 March 31 530 October 39 590 April 35 550 November 42 500 May 43 580 December 32 530 June 48 680 The annual total and monthly average figures for the year ended 30 June 2003 were as follows: Machine hours Fuel oil expense (000") (Sh. '000") Annual total 420 6,840 Monthly average 35 570 Required: (1) Using the high-low method, estimate and interpret the fixed and variable cost elements of the fuel oil expense. (ii) Using the results in (i) above, predict the fuel oil expense for November 2004 if experience indicates that 41,000 machine hours will be used. (iii) Briefly explain any two limitations of High-low method of cost estimation that may be overcome by using simple linear regression analysis.November using the FIFO method. iv) Use the regression function formulated in (ii) above to estimate the overhead cost for the month of November. QUESTION 2(a )Explain the advantages and disadvantages of the high-low method of cost estimation. (b)Central Machinery Lid. is preparing its budget for the year ending 30 June 2004. For the fuel expenses consumption it is decided to estimate an equation of the form, y = a + bx, where y is the total expense at an activity level x, a is the fixed expense and b is the rate of variable cost. The following information relate to the year ended 30 June 2003: Month Machine Fuel Oil Month Machine Fuel oil hours expense hours expense 2003 (Sh. *000") (Sh. '000") 2004 (Sh. (Sh. *000") 000% July 34 640 January 26 500 August 30 620 February 26 500 September 34 620 March 31 530 October 39 590 April 35 550 November 42 500 May 43 580 December 32 530 June 48 680 The annual total and monthly average figures for the year ended 30 June 2003 were as follows: Machine hours Fuel oil expense (*000') (Sh. '000") Annual total 420 6,840 Monthly average 35 570 Required: (1) Using the high-low method, estimate and interpret the fixed and variable cost elements of the fuel oil expense. (ii) Using the results in (i) above, predict the fuel oil expense for November 2004 if experience indicates that 41,000 machine hours will be used. (iii) Briefly explain any two limitations of High-low method of cost estimation that may be overcome by using simple linear regression analysis.The following information is provided to you for analysis: Year 2004 Equivalent production Overheads Month Units (*000") Sh.'000' January 1,425 12,185 February 950 9,875 March 1,130 10,450 April 1,690 15,280 May 1,006 9.915 June 834 9,150 July 982 10,133 August 1,259 11,981 September 1,385 12,045 October 1,420 13,180 November 1,125 13,180 December 980 10.430 Additional information: 1. In November, the opening work in progress inventory contained 1,000,000 units that were 30% complete with respect to conversion costs. 2. During the same month of November, the manufacturing department transferred 1,500,000 units. 3. The closing inventory for the month of November was 1,200,000 units and the units were 305 incomplete with respect to conversion costs 4. Using the above information, you have obtained the following variables by applying simple regression analysis. Sh. *000' Constant 3,709 Slope 6,487 Required: i) Use the high-low method to estimate the overhead cost function. ii) Use the regression method to determine the overhead cost function. iii) Compute the equivalent units of production with respect to conversion costs for the month of November using the FIFO method iv) Use the regression function formulated in (ii) above to estimate the overhead cost for the month of November.2. (i) Explain the concept of opportunity loss, and show that the (ii) (iii) minimum opportunity loss is equal to the Expected Value of Perfect Information. The failure rate in a particular examination is estimated to be 40%. Construct a table showing the probabilities of 0, 1, 2 . . . 5 students failing in a sample of ve. 150 graduate entrants are due to take their rst professional accounting exam at the Institute of Certiable Accountants. The probability distribution for the failure rate is estimated in the following table: Failure rare Probaby [1.1 0.1 0.2 0.2 0.3 0.3 0.4 0.3 0.5 0.1 Each failing student is entitled to a 10 refund on professional fees. The Institute's senior tutor is condent that she could ensure a failure rate of 0.1 by holding an intensive revision eourse, at a cost to the Institute of 300. Advise the Institute on whether the revision course should take place. A tutorial test of ve students resulted in no failures. Use this information to revise the failure rate probability distribution, and hence reassess the revision course. s. terminating? cells only bread made that day. Each loaf produced has a 1variable cost of 30p and sells for 50p. Any bread unsold at the end of each day is thrown away. At the start of each day, the manager must decide how many loaves to produce. The table below records sales over the past month: {a} {b} {'3} Daily sales Frequency Hill] ti no] 1121 1-100 1D 1600 4 Fitted costs are estimated at UK per day. Find the breakeyen number of losses produced and sold, and the number if expected daily prot was 50. Find the number of loaves produced to minimise expected opportunity loss. Bread is produced by a fully automated machine which mixes the dough, divides it into 1 ll: units, lls each halting tin and passes them through an oven. Out of each batch, some are reincted for being underweight or burnt. The proportion rejected has the probability distribution given below: Proportion rejected Probability 0.05 [1.15 [111} [l 0.15 U. 15 {i} Find the number of loaves produced it the expected num- ber of saleable loaves equals your answer to question {h}. {ii} The services of a maintenance engineer would set the rejection rate equal to 0.05, but would cost 11 per day. Adse the managtn on whether to engage the engineer or not1 if the desired daily production is 1300. 5. Cambrian Railways runs a daily container freight train between Cardiff and Birmingham. Its two major customers are British Steel and the Welsh Farming Co-operative. The demand for containers by each customer is given by the equations: P1 = 500-80, for British Steel P2 = 400-502 for Welsh farming. P; is the price charged by Cambrian per container, and @; is the number of containers used by each customer. Cambrian's total cost function is given by the equation: TC = 10 000 + 20Q where Q is the number of containers per trip. (a) What are the necessary conditions for profitable price discri- mination by Cambrian? (b) What profit-maximising rule will Cambrian use if setting prices as a discriminator? Determine the profit-maximising quantity of freight service Cambrian will supply, show how this will be divided between steel and agriculture and find the prices charged in each market. Calculate Cambrian's total profit. (c) Assume that Cambrian is prevented by law from price discri- mination. Determine Cambrian's price and output combination to maximise profit, and hence estimate the opportunity cost to Cambrian of the Anti-Price Discrimination law..1" produced has a variable cost of 30p and sells for 50p. Any bread unsold at the end of each day is thrown away. At the start of each day, the manager must decide hostr many loaves to produce. The table below records sales over the past month: Deity sales Frequency 1003 ti 1200 10 1-100 10 1600 4 (a) Fixed costs are estimated at X per day. Find the breakeven number of leaves produced and sold, and the number it" expected dain prot was 50. {b} Find the number of leaves produced to minimise expected opportunity lees. {c} Bread is produced by a fullyr automated machine which mixes the dough, divides it into 1 lb units, lls each baking tin and passes them through art oven. Out of each batch, some are rejected for being undemeight or burnt. The proportion rejected has the probabilityr distribution given below: Fmporon rejected Probebity 0.05 0.15 0.10 0.50 0.15 0.15 {i} Find the number of loaves produced if the expected num- ber of saleable loaves equals your answer to question {b}. {ii} The services of a maintenanee engineer would set the rejection rate equal to 0.05, but would cost 11 per day. Advise the manager on whether to engage the engineer or not. if the desired daily.r production is 1300. 5. (a) (b) Evaluate the operational utility of demand elasticity estimates, and outline arty interpretations! difculties in the use of such estimates. The annual demand function for a particular motor car is estimated as: D=1titll-IDPI3+ YEMEN} where D=annual demand1 P=price in Fe and Y=average disposable income. (i) Given that the retail price next year will he 12 [tilt], whilst average disposable income is expected to be 3111}, esti- mate next year's annual demand. If the manufacturer receives 313% of the retail price for each ear sold, estimate the manufacturer's revenue next year. [ii] Find the retail price to maximise manufacturer's revenue next year. {iii} If the marginal cost per car is estimated to be 50m, nd the price to maximise prot next year. (iv) 1n the subsequent year the retail priee is expected to rise to Hi] {Iii}, whilst incomes should increase by 5%. Estimate demand and manufacturer's revenue for that year, and use this information to estimate the price and income demand elasticities. 7. (a) Compare and contrast the explanatory and extrapolatery approaches to demand estimation. Illustrate your answer with reference to the problem of estimating demand for a new luxury food processor. (b) The Welsh Kitchen Design Company sells its deluxe food proces- sor for f150/unit. Company experience suggests that both price and consumer incomes affect sales, with an estimated price elasticity of demand of -3.0, whilst income elasticity is estimated at 4.0. In 1986 the company sold one million units, whilst total consumer disposable income was $600 billion. Estimated con- sumer disposable income for 1987 is f650 billion. (i) Assuming price remains the same in 1987, estimate total sales revenue. Examination questions and answer notes 339 (ii) If 1988 consumer income is expected to remain constant at (650 billion, whilst price is expected to fall by $25, estimate sales revenue in 1988 (iii) Estimate sales revenue in 1988 if consumer income rises by 10% between 1987/88, whilst price falls by 15%. (iv) Use the information above to estimate demand as a linear function of price and income