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Forecast Errors
Differences among actual results and predictions may arise from many reasons. They may arise from random influences, usual sampling errors, option of the wrong forecasting system or alpha value or only that the future conditions turn out to be radically different from the past. Whatever the cause or causes management wish to know the extent of the forecast errors and different methods exist to calculate these errors.
A commonly utilized technique, suitable to time series, is to calculate the mean squared error of the deviations between actual and forecast values then choose the forecasting system and/or parameters which gives the lowest value of mean squared errors that is akin to the 'least squares' method of establishing a regression line.
Utilizes the definition of the limit to prove the given limit. Solution In this case both L & a are zero. So, let ε 0 so that the following will be true. |x 2 - 0|
Find the series solution of2x2y”+xy’+(x2-3)Y=0 about regular singular point
Y=θ[SIN(INθ)+COS(INθ)],THEN FIND dy÷dθ. Solution) Y=θ[SIN(INθ)+COS(INθ)] applying u.v rule then dy÷dθ={[ SIN(INθ)+COS(INθ) ] dθ÷dθ }+ {θ[ d÷dθ{SIN(INθ)+COS(INθ) ] } => SI
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70 multiply 67
4 friends have 235 marbles and want to share.How many marbles should each friend receive?
Function composition: The next topic that we have to discuss here is that of function composition. The composition of f(x) & g(x) is ( f o g ) ( x ) = f ( g ( x )) In other
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