Ratio to trend

Ratio to trend Analysis

1. RATIO to TREND

2. Ratio-to-trend Method

* The ratio-to-trend method is similar to ratio-to-moving-average method
* The only difference is the way of obtaining the trend values

* Whereas in the ratio-to-moving-average method, the trend values are
obtained by the method of moving averages, in the ratio-to-trend method

* The steps in the calculation of seasonal variation are as follows :

L
2.
3.

4,

5.
6. Adjust the average ratios found in step (v) so that they will themselves average 100

Arrange the unadjusted data by years and months.

Compute the trend values for each month with the help of least squares equation.
i Og the data for each month as a percentage ratio of the corresponding trend
value.

Aggregate the January's ratios, February's ratios, etc., computed previously

Find the average ratio for each month.

per cent.

3. Problem 1

Calculate the Seasonal Index of the mentioned data with Ratio to Trend
Method

4. Problem 1

Calculate the Seasonal Index of the mentioned data with Ratio to Trend
Method

Step 1:

Year| Q1|102 | 03|04| Total | Average |TimeCode

Y x | xv | x02

1991| 36 | 34 38 | 32| 140 35 2 | -70[ 4
[1002] 38 | 48 [se [42] 186 | 465 1 [as] 1
42|56[50|52| 200 50 0 0 | 0

260 65 1 1

340 85 2 |10| 4

563 1185| 10

5. Problem 1

Calculate the Seasonal Index of the mentioned data with Ratio to Trend
Method

Step 1: [Year[at [az [as[as] Total | Average [Timecode |
Y x I Im
1991| 36| [38/32] 10 | 35 2 || a]

1992138 [as [58|42| 186 | 465 1 [465| 1

1993| 42 [ss |so|s2| 200 | 50 o | ol

1994| 56 | 7a [68 [62 | 260 | 65 1 [e [1

1995] 82 19018 180 | 340 | 5 2 [10 [4

Total 563 1185| 10

Slope: |=Sum[XY)/Sum(X*2) [=118.5/10| 11.85
Y-Intercept! =Mean(Y) 563 y= 11.85x+56.3 is the trend line

6. Problem 1

Calculate the Seasonal Index of the mentioned data with Ratio to Trend
Method

Step 2; — Y= 1185563 isthe trend ime

Year |TimeCode Trend Value Year| Q1 Q2 03 04

x Y =11.85*X+56,3 1991 =32.6-1.5-3|=32.6-1.5| =32.6+1.5|=32.6+1.5+3
1991 -2 =11.85*-2+56.3| 32.6 28.1 311 34.1 371
1992 -1 [=11.85* +56.3|44.45 1992| 3995 42.95 | 45.95 48.95
1993 0 =1185* +56.3| 56.3 1993 518 54.8 57.8 60.8
1994 1 =11.85*. +563| 68.15 1994| 63.65 66.65 | 69.65 72.65
1995 2 =11.85*- +563} 80 1995} 755 78.5 81.5 84.5

7. Problem 1

Calculate the Seasonal Index of the mentioned data with Ratio to Trend
Method

Step 3:

128.11%| 109.32% | 111.44% | 86.25%
1992| 38 | 48 | 58 | 42 | 40 | 43 | 46 | 4895 | 95.12% | 111 76% | 126.22% | 85.80%
1993| 42 | 56 | 50 | 52 [5181548578] 608 | 81.08% | 102.19% | 86.51% | 85.53%
87.98% | 111.03% | 97.63% | 85.34%
1995| 82 8 114.65% | 107.98% | 94.67%

Total | 500.90% | 548.95% | 529.77% | 437.60%
Average | 100.18% | 109.79% | 105.95% | 87.52%