effect -> affect

promql/functions.go

@@ -204,9 +204,9 @@ func calcTrendValue(i int, sf, tf float64, s, b, d []float64) float64 {
 }
 
 // Holt-Winters is similar to a weighted moving average, where historical data has exponentially less influence on the current data.
-// Holt-Winter also accounts for trends in data. The smoothing factor (0 < sf < 1) effects how historical data will effect the current
-// data. A lower smoothing factor increases the influence of historical data. The trend factor (0 < tf < 1) effects
-// how trends in historical data will effect the current data. A higher trend factor increases the influence.
+// Holt-Winter also accounts for trends in data. The smoothing factor (0 < sf < 1) affects how historical data will affect the current
+// data. A lower smoothing factor increases the influence of historical data. The trend factor (0 < tf < 1) affects
+// how trends in historical data will affect the current data. A higher trend factor increases the influence.
 // of trends. Algorithm taken from https://en.wikipedia.org/wiki/Exponential_smoothing titled: "Double exponential smoothing".
 func funcHoltWinters(ev *evaluator, args Expressions) model.Value {
 	mat := ev.evalMatrix(args[0])