Weighted Moving Average Calculator
Calculates a weighted average of the supplied recent observations. The form displays sum(weights×values)/sum(weights) beside weighted moving average, using a worked condition that can be recalculated with the labeled inputs.
Describe the observed sequence when the result is reused
Weighted moving average
Interpreting the requested weighted moving average
The weighted moving average page calculates a weighted average of the supplied recent observations.
Weighted moving average is limited to the statistical quantity named by the result panel. The weighted moving average calculation does not silently add a population, time horizon, causal direction, or decision threshold that is absent from the fields.
Inputs that define weighted moving average
- Time-series values: For weighted moving average, the displayed time-series values sequence is 12, 15, 18. Preserve time-series values order when weighted moving average depends on pairing, lag, rank, or time position, and distinguish an observed zero from a missing time-series values entry.
- Weights, oldest to newest: For weighted moving average, the displayed weights, oldest to newest sequence is 1, 2, 3. Preserve weights, oldest to newest order when weighted moving average depends on pairing, lag, rank, or time position, and distinguish an observed zero from a missing weights, oldest to newest entry.
The entries used for weighted moving average must refer to one coherent analysis condition. Combining incompatible populations, periods, or measurement definitions can produce valid weighted moving average arithmetic for a nonexistent study.
The arithmetic used for weighted moving average
For weighted moving average, match every symbol in the relationship to a labeled field before substituting numbers. Weighted moving average is reported in units.
While checking weighted moving average, use time-series values observations from one defined analysis set rather than totals copied from incompatible groups.
Worked values for weighted moving average
The default weighted moving average condition is Time-series values = 12, 15, 18, Weights, oldest to newest = 1, 2, 3.
Values 12,15,18 with weights 1,2,3 give a weighted average of 16.
The live calculator reports Weighted moving average 16. Repeating one intermediate step from sum(weights×values)/sum(weights) provides a fixed weighted moving average reference check for later code changes.
Conditions attached to weighted moving average
Weights must align with the values and their sum must be positive; larger recent weights emphasize responsiveness.
For weighted moving average, time order is part of the data. For weighted moving average, reordering observations, changing the forecast origin, or mixing incomplete seasonal cycles changes the statistical question.
A second check on weighted moving average
When interpreting weighted moving average, keep the lag, window, seasonal period, initialization rule, and forecast horizon with the result so a later calculation uses the same timeline.
As a second check for weighted moving average, outliers, ties, ordering, and missing entries can affect weighted moving average even when the number of observations stays unchanged.
A controlled sensitivity check for weighted moving average
Change time-series values while holding the remaining entries fixed, then state why the direction and size of the weighted moving average change are plausible from sum(weights×values)/sum(weights).
Repeat the weighted moving average exercise with weights, oldest to newest. If a modest defensible change materially alters the interpretation, report both conditions rather than presenting that weighted moving average scenario as exact.
Mistakes to avoid in the weighted moving average setup
Before accepting weighted moving average, compare every entered value with its label, unit, and allowed domain after reading the printed relationship from left to right.
For weighted moving average, do not substitute zero for an unobserved value; missingness and a measured zero describe different data.
Another weighted moving average failure occurs when a rounded output is reused as though it were the original measurement. Carry guard digits through calculations that depend on weighted moving average, then round only the reported value.
The surrounding workflow may also require simple moving average and exponential smoothing.
What to record with weighted moving average
Report weighted moving average using sum(weights×values)/sum(weights), followed by the entered values, units, exclusions, and analysis date. Name the weighted moving average population or dataset boundary instead of leaving it implicit.
Keep the full calculator output with the record, including Weighted moving average 16. A later weighted moving average review can then distinguish a changed input from a different convention or software implementation.
Questions about weighted moving average
Why could another program report a different weighted moving average?
A different convention for rounding, tails, ties, interpolation, parameterization, or missing values can change weighted moving average. Compare the printed weighted moving average formula and its input definitions before treating either output as wrong.
What does weighted moving average represent on this page?
It is the quantity produced by sum(weights×values)/sum(weights) from the displayed time-series values, weights, oldest to newest. This page calculates a weighted average of the supplied recent observations.
What should be saved with weighted moving average?
Save the entered values and units for time-series values, weights, oldest to newest, along with the analysis date, exclusions, software or formula version, and the relationship sum(weights×values)/sum(weights). That record is sufficient to rebuild this specific weighted moving average calculation.