Seasonal Effects (Patterns)

A regular, repeating pattern allows us to improve the accuracy of our predictions.

The long term trend will give us a general idea about what values we can expect in the future. The seasonal pattern can then be used to determine these predictions more accurately by noting the behaviour of the series in the season we are predicting values for.

Remember:

To get higher grades, you need to contextualise your findings.

Once you have performed your analysis, you will need to relate your findings back to the problem you are investigating.

i.e What do the results mean for YOUR PROBLEM.

With the seasonal pattern we are looking at what is happening in the repeating cycles. A cycle could be a week, month, quarter (3 months), year, etc. You will need to identify the highs and lows in the cycle - where they occur and how high and low each part of the cycle reaches.

For higher grades you should be giving possible reasons and link to your purpose and also think about the relative size of the season pattern to the overall variation.

For each of the graphs write a comment about the seasonal pattern.

The first two have been done for you.

Example of Seasonal Pattern description - Sea Ice

The largest amount of sea ice at the North Pole normally occurs during February and March when the amount of sea ice is approximately 4 million square kilometres above the long term trend. Between April and August there is a consistent drop from month to month as temperatures are rising. The smallest amount of sea ice regularly occurs in September where the amount of sea ice is approximately 5 million square kilometres below the long term trend. After this the temperatures start cooling down again increasing the amount of ice on a month to month basis until it returns to its peak in February and March.

Written Report (so far)

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