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a and 2.b:

2.a) Forecasting Production

To determine the projected forecast, we will use linear regression based on the historical data. Let XX be the year number and YY be the production amount. The linear regression equation is Y=aX+bY = aX + b.

  • Data for Total Production: Years (XX): 1,2,3,4,51, 2, 3, 4, 5 Total Production (YY): 200,000,250,000,295,000,340,000,390,000200,000, 250,000, 295,000, 340,000, 390,000

  • Data for Quarter Two Production: Years (XX): 1,2,3,4,51, 2, 3, 4, 5 Quarter Two Production (YQ2Y_{Q2}): 45,000,55,000,70,000,80,000,100,00045,000, 55,000, 70,000, 80,000, 100,000

  • Data for Quarter Three Production: Years (XX): 1,2,3,4,51, 2, 3, 4, 5 Quarter Three Production (YQ3Y_{Q3}): 65,000,80,000,90,000,100,000,95,00065,000, 80,000, 90,000, 100,000, 95,000

For linear regression, we calculate:
∑X=1+2+3+4+5=15\sum X = 1+2+3+4+5 = 15
∑X2=12+22+32+42+52=55\sum X^2 = 1^2+2^2+3^2+4^2+5^2 = 55
The slope bb and intercept aa are given by:

b=n∑XY−∑X∑Yn∑X2−(∑X)2b = \frac{n \sum XY - \sum X \sum Y}{n \sum X^2 - (\sum X)^2} a=∑Y−b∑Xna = \frac{\sum Y - b \sum X}{n}

2.a (i) Determine the projected forecast for the seventh year.

  1. Calculate ∑Y\sum Y and ∑XY\sum XY for total production.

    ∑Y=200,000+250,000+295,000+340,000+390,000=1,475,000\sum Y = 200,000 + 250,000 + 295,000 + 340,000 + 390,000 = 1,475,000
    ∑XY=1(200,000)+2(250,000)+3(295,000)+4(340,000)+5(390,000)\sum XY = 1(200,000) + 2(250,000) + 3(295,000) + 4(340,000) + 5(390,000)
    ∑XY=200,000+500,000+885,000+1,360,000+1,950,000=4,895,000\sum XY = 200,000 + 500,000 + 885,000 + 1,360,000 + 1,950,000 = 4,895,000

  2. Calculate the slope bb and intercept aa for total production.

    b=5(4,895,000)−15(1,475,000)5(55)−(15)2=24,475,000−22,125,000275−225=2,350,00050=47,000b = \frac{5(4,895,000) - 15(1,475,000)}{5(55) - (15)^2} = \frac{24,475,000 - 22,125,000}{275 - 225} = \frac{2,350,000}{50} = 47,000 a=1,475,000−47,000(15)5=1,475,000−705,0005=770,0005=154,000a = \frac{1,475,000 - 47,000(15)}{5} = \frac{1,475,000 - 705,000}{5} = \frac{770,000}{5} = 154,000

    The regression equation is Y=47,000X+154,000Y = 47,000X + 154,000.

  3. Forecast for the seventh year (X=7X=7).

    Y7=47,000(7)+154,000=329,000+154,000=483,000Y_7 = 47,000(7) + 154,000 = 329,000 + 154,000 = 483,000

    The projected forecast for the seventh year is 483,000 units\boxed{\text{483,000 units}}.

    2.a (ii) Determine the project production for the 2nd and 3rd quarters in the seventh year.

  4. Calculate ∑YQ2\sum Y_{Q2} and ∑XYQ2\sum XY_{Q2} for Quarter Two production.

    ∑YQ2=45,000+55,000+70,000+80,000+100,000=350,000\sum Y_{Q2} = 45,000 + 55,000 + 70,000 + 80,000 + 100,000 = 350,000
    ∑XYQ2=1(45,000)+2(55,000)+3(70,000)+4(80,000)+5(100,000)\sum XY_{Q2} = 1(45,000) + 2(55,000) + 3(70,000) + 4(80,000) + 5(100,000)
    ∑XYQ2=45,000+110,000+210,000+320,000+500,000=1,185,000\sum XY_{Q2} = 45,000 + 110,000 + 210,000 + 320,000 + 500,000 = 1,185,000

  5. Calculate the slope bQ2b_{Q2} and intercept aQ2a_{Q2} for Quarter Two.

    bQ2=5(1,185,000)−15(350,000)5(55)−(15)2=5,925,000−5,250,00050=675,00050=13,500b_{Q2} = \frac{5(1,185,000) - 15(350,000)}{5(55) - (15)^2} = \frac{5,925,000 - 5,250,000}{50} = \frac{675,000}{50} = 13,500 aQ2=350,000−13,500(15)5=350,000−202,5005=147,5005=29,500a_{Q2} = \frac{350,000 - 13,500(15)}{5} = \frac{350,000 - 202,500}{5} = \frac{147,500}{5} = 29,500

    The regression equation for Q2 is YQ2=13,500X+29,500Y_{Q2} = 13,500X + 29,500.

  6. Forecast for Quarter Two in the seventh year (X=7X=7).

    YQ2,7=13,500(7)+29,500=94,500+29,500=124,000Y_{Q2,7} = 13,500(7) + 29,500 = 94,500 + 29,500 = 124,000

    The projected production for the 2nd quarter in the seventh year is 124,000 units\boxed{\text{124,000 units}}.

  7. Calculate ∑YQ3\sum Y_{Q3} and ∑XYQ3\sum XY_{Q3} for Quarter Three production.

    ∑YQ3=65,000+80,000+90,000+100,000+95,000=430,000\sum Y_{Q3} = 65,000 + 80,000 + 90,000 + 100,000 + 95,000 = 430,000
    ∑XYQ3=1(65,000)+2(80,000)+3(90,000)+4(100,000)+5(95,000)\sum XY_{Q3} = 1(65,000) + 2(80,000) + 3(90,000) + 4(100,000) + 5(95,000)
    ∑XYQ3=65,000+160,000+270,000+400,000+475,000=1,370,000\sum XY_{Q3} = 65,000 + 160,000 + 270,000 + 400,000 + 475,000 = 1,370,000

  8. Calculate the slope bQ3b_{Q3} and intercept aQ3a_{Q3} for Quarter Three.

    bQ3=5(1,370,000)−15(430,000)5(55)−(15)2=6,850,000−6,450,00050=400,00050=8,000b_{Q3} = \frac{5(1,370,000) - 15(430,000)}{5(55) - (15)^2} = \frac{6,850,000 - 6,450,000}{50} = \frac{400,000}{50} = 8,000 aQ3=430,000−8,000(15)5=430,000−120,0005=310,0005=62,000a_{Q3} = \frac{430,000 - 8,000(15)}{5} = \frac{430,000 - 120,000}{5} = \frac{310,000}{5} = 62,000

    The regression equation for Q3 is YQ3=8,000X+62,000Y_{Q3} = 8,000X + 62,000.

  9. Forecast for Quarter Three in the seventh year (X=7X=7).

    YQ3,7=8,000(7)+62,000=56,000+62,000=118,000Y_{Q3,7} = 8,000(7) + 62,000 = 56,000 + 62,000 = 118,000

    The projected production for the 3rd quarter in the seventh year is 118,000 units\boxed{\text{118,000 units}}.

    2.b) Define the following appraisal indicators:

    • i) Net Present Value (NPV) The Net Present Value (NPV) is the difference between the present value of cash inflows and the present value of cash outflows over a period of time. It is a capital budgeting technique used to assess the profitability of a project or investment. A positive NPV indicates that the project is expected to generate more value than its cost, making it a potentially desirable investment.

    • ii) Payback Period (PBP) The Payback Period (PBP) is the amount of time required for an investment to generate enough cash inflows to recover its initial cost. It is a simple method to evaluate the risk and liquidity of a project, with shorter payback periods generally preferred as they imply faster recovery of capital and lower risk exposure.

    • iii) Cash Flow (CF) Cash Flow refers to the net amount of cash and cash equivalents moving into and out of a business or project. It represents the actual movement of money, distinguishing it from accounting profit. Cash flow is vital for assessing a company's liquidity and solvency, and it is typically categorized into operating, investing, and financing activities.

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