Yi(Sales) Forecast 4.8 4.89 4.1 4.52 6.05 6.5 6.53 5.8 5.44 S.2 5.01 6.8 6.69 7.4 98 63 5,99 SUMMARY OUTPUT Regression Sentidics Multiple R 0.95899 R Square 091967 Adjusted R Square 0.91393 Standard Ener 0.21346 Observations 16 ANOVA Significance SS MS Regression 7.302797 3028 160.276 4.6903E-09 Residual 14 0.637890.0456 Total 15 794069 Standard Coefficients Error Stat P-value Lower 95%% 93%% Lower 95.0%, Upper 95.07 Intercept 5.09899 0.1119445.3521.3E-16 4.85890361 5.33907 4.858903608 5.33907 0.14656 0.01158 12 664 7E-09 0.12172775 0.17139 0.121727734 0.17139 From table of sales forecast and the excel summary sheet attached, calculate: Derive the trend Calculate all the error types available (e.g. MAD, MSE, MAPE, RSFE, TS etc.) Explain the figures you arrived at and their applicability