Do you need to model a process that has a trend or seasonal variation? SPC for Excel contains the following basic time series analysis:
Linear
Quadratic
Exponential Growth
Single Exponential Growth
Double Exponential Growth
Winter's Method
Moving Average
See What Time Series analysis in SPC for Excel Can Do!
Why Use Time Series Analysis in SPC for Excel?
SPC for Excel easily performs time series analysis using one of the above techniques. A time series is a series of data points in time order, taken at successive equally spaced points in time, such as daily, yearly, etc. A time series is plotted over time as a run chart. There are potentially three components in a time series analysis: level, trend and seasonal.
One use of time series analysis is to forecast future values based on history.
Another objective is to find patterns in the data that can be used to extrapolate those patterns into the future.
Get These Time Series Analysis Features
Compare models using mean absolute percentage error (MAPE), mean absolute deviation (MAD), or mean squared deviation (MSD)
Forecast future points
Includes prediction limits for future points
Enter values for level, trend or forecast weights or let SPC for Excel find them by minimizing the error