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ACCA P3 Chapter 27 Forecasting

VIVA

ACCA P3 lectures Download ACCA P3 notes


Reader Interactions

Comments

  1. kutukova says

    March 15, 2019 at 1:45 am

    Hi,

    Could I double check whether have understood the principle of time series method for the forecast correctly?

    Forecast for Q3 Year 4

    2,451 – (38.4*5) + 4= 2,255

    Thank you in advance

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    • Ken Garrett says

      March 15, 2019 at 9:38 am

      That’s right, but why are you studying P3? It’s no longer on the syllabus.

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  2. samindramummina says

    June 2, 2017 at 2:23 pm

    The Seasonal Variation for Q2 is 95 not 96.

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  3. Jens says

    May 15, 2017 at 9:19 pm

    Very nice lecture, thank you!

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  4. sa1pw says

    May 7, 2017 at 8:19 pm

    Will the examiner provide formula for Coefficient of Correlation and Coefficient of determination?

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  5. tommy says

    October 6, 2016 at 12:17 am

    can we be asked to draw decision trees in p3?

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    • Ken Garrett says

      October 6, 2016 at 1:03 pm

      Yes – simple ones. See December 2012 Q4 (a)

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    • checubara2011 says

      November 4, 2016 at 1:30 pm

      YES

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  6. Milan says

    January 5, 2016 at 10:52 pm

    Dear Sir,

    Is scenario planning an important element of p3 syllabus or should it be only learned up – to the definational knowledge level?

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    • Ken Garrett says

      January 6, 2016 at 2:39 pm

      It has never been tested much. Know what it is. If you have to apply it you will be guided and constrained by the information in the question.

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  7. Ken Garrett says

    November 16, 2015 at 7:38 am

    It is explained in the lecture.

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  8. pbtpriyantha says

    November 16, 2015 at 6:18 am

    Dear Sir,
    Hi….

    Can you please explain me what ‘s the relationship of coefficient of correlation (r) and Coefficient determination (r2= rXr) with Linear regression (y= ax+b)…

    Thanks in advance

    BR,
    Priyantha

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    • td4mee says

      May 8, 2017 at 3:44 am

      y=ax+b is the actual forecasting tool, where you substitute x etc.

      r and r2 more speaks to the accuracy of the forecast in an arbitrary way.

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