Data considerations for Box-Cox Transformation for Time Series

To ensure that your results are valid, consider the following guidelines when you collect data, perform the analysis, and interpret your results.

Data must be for continuous variables

You can use the Box-Cox transformation with continuous time series data. The Box-Cox transformation is not appropriate for categorical data.

Record data in chronological order

Time series data are collected at regular intervals and are recorded in time order. You should record the data in the worksheet in the same order that you collect it. If the data are not in chronological order, you cannot assess time-related patterns in the data. However, you can still use Scatterplot to investigate the relationship between a pair of continuous variables.

Collect data at appropriate time intervals

Choose the time interval based on the patterns that you want to detect. For example, to look for month-to-month patterns in a process, collect data at the same time each month. If you collect data each week, then the monthly pattern may be lost in the noise of the weekly data. If you collect data each quarter, the monthly pattern may be lost when it is averaged out in each quarter.

If you are looking only for general trends or shifts in the data over time, and not for patterns associated with a specific time interval, the length of the interval is less important.

All values must be greater than 0

To use a Box-Cox transformation with data that are less than 0, manually transform the data. Add the same constant value to all the data points so that all values are greater than 0. To view the data in the original units after the Box-Cox transformation, reverse the Box-Cox transformation and then subtract the constant.