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CIMA - P1 > Forecasting Sales Volumes > Flashcards

Forecasting Sales Volumes Flashcards

1
Q

What is time series analysis?

A

A mathematical technique for analyzing past observations to forecast future impacts.

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2
Q

What are the four components of time series analysis?

A
  • Long-term trend (T)
  • Seasonal component (S)
  • Cyclical variation (C)
  • Random variation (R)
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3
Q

What does the long-term trend (T) represent?

A

The underlying direction and quantity of change over the long term.

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4
Q

What influences the long-term trend?

A
  • Demographics
  • Technological advancements
  • Changes in lifestyles
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5
Q

Define a linear trend.

A

A straight line trend represented by the equation T = a + bt.

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6
Q

What is a logistic trend characterized by?

A

Slow growth followed by a spurt and then stagnation.

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7
Q

What is an exponential trend and how is it represented?

A

A growth pattern like compound interest, represented by T = (1 + r)^t.

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8
Q

Fill in the blank: Seasonal variations (S) are best described as _______.

A

[short-term trends and fluctuations due to seasonal circumstances]

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9
Q

What are cyclical variations (C)?

A

Variations that occur over a longer period, often associated with economic cycles.

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10
Q

True or False: Random variations (R) can be forecasted.

A

False

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11
Q

What is the easiest method to identify a trend?

A

Plotting observations on a graph and drawing a ‘line of best fit’.

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12
Q

What is an additive model in time series analysis?

A

Y = T + S + C + R, simplified to Y = T + S in exams.

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13
Q

How is the seasonal variation calculated in an additive model?

A

S = Y - T.

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14
Q

What does the multiplicative model represent?

A

Y = T x S x C x R, simplified to Y = T x S in exams.

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15
Q

How is the seasonal variation calculated in a multiplicative model?

A

S = Y / T.

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16
Q

Provide an example of seasonal variations.

A
  • Higher sales of sun cream in summer
  • Increased sales of scarves in winter
  • Sales increases around holidays
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17
Q

What is the equation for exponential growth?

A

T = (1 + r)^t.

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18
Q

What is meant by adjusted values in time series analysis?

A

Forecasted figures that represent underlying trend values adjusted for seasonal variations.

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19
Q

What is the definition of adjusted values in forecasting?

A

Adjusted values represent the underlying trend values, adjusted for any seasonal variation.

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20
Q

In the equation y = 100 + 25x, what does ‘y’ represent?

A

Sales in units.

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21
Q

In the equation y = 100 + 25x, what does ‘x’ represent?

A

The quarter number.

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22
Q

How do you calculate the trend for a given quarter?

A

Set the x value equal to the quarter number and calculate the y value using the equation.

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23
Q

What is the formula for additive seasonal variation?

A

S = Y - T, where Y is actual sales and T is trend sales.

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24
Q

What is the additive variation for Quarter 1 if actual sales are 135 and the trend is 125?

A

10.

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25
Q

What is the formula for multiplicative seasonal variation?

A

S = Y / T.

26
Q

What does a multiplicative seasonal variation of 1.08 indicate?

A

The number of units sold was 8% higher than the trend.

27
Q

What are the forecast sales for Quarter 5 using the additive model?

A

235 units.

28
Q

What are the forecast sales for Quarter 5 using the multiplicative model?

A

243 units.

29
Q

True or False: The additive model assumes seasonal variations remain constant over time.

30
Q

True or False: The multiplicative model is generally considered superior to the additive model.

31
Q

What is the formula for the trend line in linear regression?

A

T = a + bt.

32
Q

In the regression formula T = a + bt, what does ‘a’ represent?

A

The point at which the trend line intersects the vertical y-axis (at t = 0).

33
Q

In the regression formula T = a + bt, what does ‘b’ represent?

A

The increase (or decrease) in one time period.

34
Q

What does the symbol ∑ represent in regression analysis?

A

The ‘sum of’.

35
Q

What is the least squares formula used for in linear regression?

A

To calculate the values of ‘a’ and ‘b’ for the trend line.

36
Q

What is the time period represented by ‘t’ in the trend line formula?

A

The time period, starting from t = 1 for the first quarter.

37
Q

What is the trend forecast for Q2 of 20X4 if t = 18?

38
Q

What would be the average of the y values (ȳ) if ∑y = 790.3 and n = 16?

39
Q

What would be the average of the x values (x̄) if ∑x = 136 and n = 16?

40
Q

What is the formula for calculating seasonal variation in the additive model?

A

Seasonal variation = Actual Value – Trend

41
Q

What is the formula for calculating seasonal variation in the multiplicative model?

A

Seasonal variation = Actual Value / Trend

42
Q

What are the average seasonal variations for each quarter?

A
  • Q1: 0.83
  • Q2: 1.00
  • Q3: 0.96
  • Q4: 1.21
43
Q

What is the formula for forecasted values using the multiplicative model?

A

Actual (forecasted) values (Y) = Trend (T) x Seasonal variation (S)

44
Q

What is the forecasted value for 20X4 Q1?

45
Q

What is the forecasted value for 20X4 Q2?

46
Q

What is the forecasted value for 20X4 Q3?

47
Q

What is the forecasted value for 20X4 Q4?

48
Q

What indicates a perfect correlation between two variables?

A

The line of best fit runs exactly through all of the points in the data set

49
Q

What indicates a partial correlation between two variables?

A

A generally increasing or decreasing trend with some variation

50
Q

What indicates no correlation between two variables?

A

No evidence of a relationship; points appear unrelated

51
Q

What is the correlation coefficient represented by?

52
Q

What does a correlation coefficient value close to 1 indicate?

A

A strong positive correlation

53
Q

What does a correlation coefficient value close to 0 indicate?

A

No correlation between the variables

54
Q

What does a correlation coefficient value close to -1 indicate?

A

A strong negative correlation

55
Q

How is the coefficient of determination calculated?

A

Coefficient of determination = r²

56
Q

What does a coefficient of determination of 0 indicate?

A

No relationship between changes in X and Y

57
Q

What does a coefficient of determination of 1 indicate?

A

Change in Y is solely due to change in X

58
Q

What is the rank correlation coefficient also known as?

A

Spearman’s rank correlation coefficient

59
Q

What does the rank correlation coefficient measure?

A

The correlation between the rankings of two distributions

60
Q

What is the formula for calculating the rank correlation coefficient?

A

Rs = 1 - (6 ∑d²) / (n(n² - 1))

61
Q

What does a rank correlation coefficient close to 1 indicate?

A

A strong correlation between rankings

62
Q

What can be concluded from a rank correlation coefficient of 0.636?

A

There is some correlation between productivity and happiness, but it is low

CIMA - P1 (7 decks)

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