Business Decisions Analysis

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How is forecast error calculated?

 

 

SKU: Buss020304(1)

QUESTION 1

Analysis and Cost Estimation

Deborah, the accountant at Plus Plastics wants to identify cost drivers for support overhead costs. She has the impression that the staff spend a large part of their time ensuring that the equipment is correctly set up and checking the first units of production in each batch. Deborah has collected the following data for the past 12 months:
A

a)Using the high-low method estimate the cost equation using machine hours as the independent variable. Then use your equation to predict support overhead costs (to the nearest $) for a month in which 3,000 machine hours were used? (Round b-value to nearest cent.)

(b) Using Excel, perform three regression analyses to regress overhead cost against (1) MH, (2) Batches, then (3) against both independent variables simultaneously. State the cost equation from each. Analyse and comment on the results of each regression as you perform it, stating the cost equation, and in your analysis/comments refer to economic plausibility, goodness of fit, and statistical significance of the independent variables. Determine the best one to use as a basis for future use and explain why you chose that one.

 

QUESTION 2 

  Forecasting     

(a)  All forecasts are never 100% accurate but subject to error.

1 How is forecast error calculated?

2 Identify and describe three common measures of forecast error. Then illustrate how each is calculated by constructing a 4-period example.
(b)Consider the following table of monthly sales of car tyres by a local company:

January     300
February   350
March      500
April        550
May        400
June        ?   

1.Using a 2-month moving average develop forecasts sales for March to June inclusive.

2.Using a 2-month weighted moving average, with weights of 2 for the most recent month and 1 for the previous month develop forecasts sales for March to June inclusive.

3.The sales manager had predicted sales for January of 400 units. Using exponential smoothing with a weight of 0.1 develop forecasts sales for March to June inclusive.

4.Which of the three techniques gives the most accurate forecasts? How do you know?

 

(c)Describe the four patterns typically found in time series data. What is meant by the expression “decomposition” with regard to forecasting? Briefly describe the process.

 

 QUESTION 3   

CVP Analysis   

(a)A small factory, Pollution Control Pty Ltd, is currently engaged in the manufacture of a single product, precision fuel injectors. These fuel injectors sell for $300 per car. Costs of production include direct materials $100, direct labour 4 hours at $20 per hour, and variable overhead of $10 per direct labour hour. All other costs are fixed and total $4800 per month.

Calculate the number of fuel injectors that must be produced and sold per month for Pollution Control to break even?

(b) The proprietor, Mr S. Jones, decides that profits can be increased and risks reduced by adding a second product. He plans to also produce electronic ignition sets to sell for $140 each. He decides that the product mix should be 3 fuel injectors to 1 ignition set. The costs of producing the ignition set are:

Direct materials      $50 per set
Direct labour           2 hours at $20 per hour
Variable overhead   $5 per direct labour hour

How many fuel injectors and ignition sets must be produced and sold to yield a net profit of $3500 per month after tax, given a tax rate of 30c in the dollar?

(c) Alpha Company produces a single product, Beta, which has the following unit selling price and costs:

Selling price per unit       $2000
Variable costs per unit    $1500
Fixed costs per annum   $2 000 000

Prices and costs are certain, but annual demand is uncertain. It is thought that annual demand is normally distributed with expected sales of 6000 units and a standard deviation of 1000 units.

1.Calculate expected annual profit.
2 What is the standard deviation of expected profit?
3. Calculate the probability of at least breaking even.

 

 

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