Goodness of Fit
Correlation0.6582
R-squared0.4332
RMSE31.7846


Actuals, Predictions, and Residuals
#ActualsForecastsResiduals
102.29411764705882-2.29411764705882
262.294117647058823.70588235294118
312.29411764705882-1.29411764705882
46496.5-32.5
548.53846153846154-4.53846153846154
602.29411764705882-2.29411764705882
7028.5384615384615-28.5384615384615
848.53846153846154-4.53846153846154
902.29411764705882-2.29411764705882
1002.29411764705882-2.29411764705882
1102.29411764705882-2.29411764705882
1202.29411764705882-2.29411764705882
1302.29411764705882-2.29411764705882
144796.5-49.5
1502.29411764705882-2.29411764705882
1602.29411764705882-2.29411764705882
1712.29411764705882-1.29411764705882
1802.29411764705882-2.29411764705882
199396.5-3.5
2002.29411764705882-2.29411764705882
21118.538461538461542.46153846153846
2202.29411764705882-2.29411764705882
2302.29411764705882-2.29411764705882
24028.5384615384615-28.5384615384615
2502.29411764705882-2.29411764705882
2668.53846153846154-2.53846153846154
2702.29411764705882-2.29411764705882
28118.538461538461542.46153846153846
296628.538461538461537.4615384615385
3002.29411764705882-2.29411764705882
3123596.5138.5
3212.29411764705882-1.29411764705882
334396.5-53.5
34102.294117647058827.70588235294118
3502.29411764705882-2.29411764705882
3602.29411764705882-2.29411764705882
3702.29411764705882-2.29411764705882
3802.29411764705882-2.29411764705882
39862.2941176470588283.7058823529412
4008.53846153846154-8.53846153846154
41028.5384615384615-28.5384615384615
421528.5384615384615-13.5384615384615
4378.53846153846154-1.53846153846154
4438.53846153846154-5.53846153846154
454828.538461538461519.4615384615385
4672.294117647058824.70588235294118
474296.5-54.5
4802.29411764705882-2.29411764705882
49202.2941176470588217.7058823529412
508296.5-14.5
5102.29411764705882-2.29411764705882
5252.294117647058822.70588235294118
5302.29411764705882-2.29411764705882
5402.29411764705882-2.29411764705882
5502.29411764705882-2.29411764705882
5612.29411764705882-1.29411764705882
5702.29411764705882-2.29411764705882
5802.29411764705882-2.29411764705882
5902.29411764705882-2.29411764705882
60228.5384615384615-26.5384615384615
6122.29411764705882-0.294117647058823
6282.294117647058825.70588235294118
6302.29411764705882-2.29411764705882
6442.294117647058821.70588235294118
6502.29411764705882-2.29411764705882
662996.5-67.5
67188.538461538461549.46153846153846
6802.29411764705882-2.29411764705882
69198.5384615384615410.4615384615385
7008.53846153846154-8.53846153846154
71128.5384615384615-27.5384615384615
7202.29411764705882-2.29411764705882
7302.29411764705882-2.29411764705882
7402.29411764705882-2.29411764705882
7514028.5384615384615111.461538461538
76128.5384615384615-27.5384615384615
7702.29411764705882-2.29411764705882
784096.5-56.5
7902.29411764705882-2.29411764705882
8002.29411764705882-2.29411764705882
8102.29411764705882-2.29411764705882
8202.29411764705882-2.29411764705882
8342.294117647058821.70588235294118
848128.538461538461552.4615384615385
8502.29411764705882-2.29411764705882
8602.29411764705882-2.29411764705882
8702.29411764705882-2.29411764705882
8802.29411764705882-2.29411764705882
89238.5384615384615414.4615384615385
9058.53846153846154-3.53846153846154
9102.29411764705882-2.29411764705882
92128.5384615384615-27.5384615384615
9302.29411764705882-2.29411764705882
9402.29411764705882-2.29411764705882
9502.29411764705882-2.29411764705882
9602.29411764705882-2.29411764705882
971628.5384615384615-12.5384615384615
9802.29411764705882-2.29411764705882
9902.29411764705882-2.29411764705882
10029096.5193.5
10102.29411764705882-2.29411764705882
10202.29411764705882-2.29411764705882
10302.29411764705882-2.29411764705882
10402.29411764705882-2.29411764705882