Time Series Analysis 2

The sum of Seasonal Indices based on monthly data over a year should be

• Calculated from the value of the season divided by the seasonal average

• Dependent on the actual sales

• The same as the quarterly average

• 12 (or 12.001 or 11.999 depending on rounding errors)

Deseasonalised Data can be found by:

• Dividing actual sales by the seasonal index

• Dividing the seasonal index by the actual sales

• multiplying seasonal index by the actual sales

• multiplying the seasonal index by the deseasonalisted data

The actual figure can be found by...

• Dividing the deseasonalised figure by the seasonal index

• Dividing the seasonal index by the deseasonalised figure

• Multiplying the deseasonalised figure by the seasonal index

• Dividing the data value by the seasonal average

In Q1 the SI was 0.8;

in Q2 the SI was 1.2;

in Q3 the SI was 0.3;

So in Q4 the SI was...

• 0.7

• 2.3

• 2.7

• 1.7

In Q1 the SI was 0.5;

in Q2 the SI was 0.8;

in Q3 the SI was 1.3;

So in Q4 the SI was 1.4;

What can be said about the data:

• It is cyclic

• There is no trend

• There is a positive trend

• There is a negative trend

In Year 1, a company's sales were $920K

In Year 2, a company's sales increased to $1241K

In Year 3, a company's sales were $1085K

In Year 4, a company's sales were 10% higher

Use your calculator to identify the correct trend line

• y=943.75+66.45x

• y=943750+66450x

• y=943.75x+66.45

• y=943750x+66450

How confident should you be in interpolating data from the previous question?

• Highly confident

• Moderately confident

• Not confident

• As it is cyc;lic, it is a given that interpolating is accurate at over 85% confidence