A 12-point moving average should be used to estimate the trend for a monthly time series with a strong seasonal pattern.

Here's why:

A moving average is a simple technique that smooths out price data by creating a constantly updated average price. In the context of time series analysis, it is used to remove short-term fluctuations, thus helping to identify the direction of the trend.

A 12-point moving average is particularly suitable for a monthly time series with a strong seasonal pattern because it can capture the trend while smoothing out the seasonal fluctuations. This is because there are 12 months in a year, so a 12-point moving average would cover an entire year's worth of data. This allows the moving average to account for any seasonal patterns that occur on a yearly basis.

The other options are not as suitable. A centred 11-point or 13-point moving average would not align as well with the 12-month seasonal pattern. A 2x12-point moving average, while it would cover two years' worth of data, might be too broad and could potentially smooth out some of the trend information.

Question

A 12-point moving average should be used to estimate the trend for a monthly time series with a strong seasonal pattern.

Here's why:

A moving average is a simple technique that smooths out price data by creating a constantly updated average price. In the context of time series analysis, it is used to remove short-term fluctuations, thus helping to identify the direction of the trend.

A 12-point moving average is particularly suitable for a monthly time series with a strong seasonal pattern because it can capture the trend while smoothing out the seasonal fluctuations. This is because there are 12 months in a year, so a 12-point moving average would cover an entire year's worth of data. This allows the moving average to account for any seasonal patterns that occur on a yearly basis.

The other options are not as suitable. A centred 11-point or 13-point moving average would not align as well with the 12-month seasonal pattern. A 2x12-point moving average, while it would cover two years' worth of data, might be too broad and could potentially smooth out some of the trend information.

Knowee AI · Accepted Answer

A 12-point moving average should be used to estimate the trend for a monthly time series with a strong seasonal pattern.

Here's why:

A moving average is a simple technique that smooths out price data by creating a constantly updated average price. In the context of time series analysis, it is used to remove short-term fluctuations, thus helping to identify the direction of the trend.

A 12-point moving average is particularly suitable for a monthly time series with a strong seasonal pattern because it can capture the trend while smoothing out the seasonal fluctuations. This is because there are 12 months in a year, so a 12-point moving average would cover an entire year's worth of data. This allows the moving average to account for any seasonal patterns that occur on a yearly basis.

The other options are not as suitable. A centred 11-point or 13-point moving average would not align as well with the 12-month seasonal pattern. A 2x12-point moving average, while it would cover two years' worth of data, might be too broad and could potentially smooth out some of the trend information.

For a monthly time series with a strong seasonal pattern, which of the following moving averages should be used to estimate the trend?Group of answer choicesa centred 11-point moving averagea 12-point moving averagea 2x12-point moving averagea centred 13-point moving average

Question

Solution

Similar Questions

Upgrade your grade with Knowee