Which of the following values of the smoothing constant would cause exponential smoothing to respond the slowest to forecast errors (i. e., less error would be factored into subsequent forecasts)?

a. 0.1
b. 0.4
c. 0.2
d. 0.3

b

Step-by-step explanation:

Exponential smoothing is a time series forecasting approach for univariate data that can be extended to assist data with a systematic trend or seasonal element.

Forecast for next month is given by

where

If value of approaches to 1 then it can be said that it is very responsive

and it is close to 0 then it is stable.

So correct answer is 0.4 i.e. option b

answer:  

step-by-step explanation:

here x represents the height of the pole,

and, the height of the shadow of the pole is 12 feet.

also, the angle of elevation from the top of the pole is 40°,

therefore,

by the low of sine,

which is the required equation for finding the value of x,

solution:

→c= a b , that is product of a and b is possible only when when a is m × n matrix and b is n × p matrix.

that is, number of columns of a= number of rows of b.

so, size of matrix , c= a b is , if a = (m × n)matrix

b= (n × p)matrix

then a b = [ (m × n)matrix] ×[   (n × p)matrix ]

→→c= a b= [m × p ] matrix

→→size of product a b will be equal to = number of rows of a × number of columns of b