Why do you think using computer software to do forecasting calculations is almost necessary if you are changing the number of time periods for a moving average or the alpha value for an exponential smoothing calculation

There are two major methods of forecasting

One is the Causal method and the 2nd one is the times series method

Causal method mainly tries to find out cause and effect relation between variable and various factors impacting that variable while the time series method infuences the utilization of the historical data and mainly focus to forecast based on the trend present. It simply ignores the other variables. It just tries to give an idea of a trend, it can't predict the impact of other variables as in causal method.

Linear regression analysis can be utilized in both sort of estimating technique. By linear regression analysis we can anticipate effect of different factor on factor variable. It anticipate the pattern, yet additionally gives an idea about connection among variable and different elements affecting it. That is the reason Linear regression is considered as best technique for forecasting.  

Presently, going to the next part of this inquiry, Time period utilized in moving normal is settled based on fluctuation showing up in how much period, to smoothen out the variation. Also, Alpha value is chosen dependent on the time span to smoothen out the variation in the information. Changing of time-frame or distinctive alpha will make estimation complex. And furthermore, it will make computation more probabilistic as opposed to deterministic which may create mistake whenever done by manual calculation. That is the reason program are important in such sort of computation

1. credits

2. dual - aspect

hope i : )

i leave the calculator work to you.

7. diameter 4 miles, circumference 4π miles

8. radius 0.2 miles, circumference 0.4π miles

[this is a bad problem because the actual radius of a car on the track is less than 0.2 miles so the answer is less than 0.4π miles]

9. radius 6 feet, circumference 12π feet

10. diameter 14 cm, circumference 14π cm

11. diameter 4.8 feet, circumference 4.8π feet