Multiple Linear Regression - Estimated Regression Equation
y[t] = + 99.5657894736842 + 10.1961152882206x[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)99.56578947368421.90059752.386600
x10.19611528822062.6230733.88710.0002120.000106


Multiple Linear Regression - Regression Statistics
Multiple R0.40283525888397
R-squared0.162276245800115
Adjusted R-squared0.151536197669348
F-TEST (value)15.1094523808726
F-TEST (DF numerator)1
F-TEST (DF denominator)78
p-value0.000211700505996726
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation11.7160664254836
Sum Squared Residuals10706.7645739348


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1106.799.56578947368467.13421052631544
2110.299.565789473684210.6342105263158
3125.999.565789473684226.3342105263158
4100.199.56578947368420.534210526315793
5106.499.56578947368426.8342105263158
6114.899.565789473684215.2342105263158
781.399.5657894736842-18.2657894736842
88799.5657894736842-12.5657894736842
9104.299.56578947368424.6342105263158
1010899.56578947368428.4342105263158
1110599.56578947368425.4342105263158
1294.599.5657894736842-5.0657894736842
139299.5657894736842-7.5657894736842
1495.999.5657894736842-3.66578947368420
15108.899.56578947368429.2342105263158
16103.499.56578947368423.83421052631580
17102.199.56578947368422.53421052631579
18110.199.565789473684210.5342105263158
1983.299.5657894736842-16.3657894736842
2082.799.5657894736842-16.8657894736842
21106.899.56578947368427.2342105263158
22113.799.565789473684214.1342105263158
23102.599.56578947368422.9342105263158
2496.699.5657894736842-2.96578947368421
2592.199.5657894736842-7.4657894736842
2695.699.5657894736842-3.96578947368421
27102.399.56578947368422.73421052631580
2898.699.5657894736842-0.965789473684207
2998.299.5657894736842-1.36578947368420
30104.599.56578947368424.9342105263158
318499.5657894736842-15.5657894736842
3273.899.5657894736842-25.7657894736842
33103.999.56578947368424.33421052631580
3410699.56578947368426.4342105263158
3597.299.5657894736842-2.3657894736842
36102.699.56578947368423.03421052631579
378999.5657894736842-10.5657894736842
3893.899.5657894736842-5.7657894736842
39116.7109.7619047619056.93809523809524
40106.8109.761904761905-2.96190476190477
4198.5109.761904761905-11.2619047619048
42118.7109.7619047619058.93809523809524
4390109.761904761905-19.7619047619048
4491.9109.761904761905-17.8619047619048
45113.3109.7619047619053.53809523809523
46113.1109.7619047619053.33809523809523
47104.1109.761904761905-5.66190476190477
48108.7109.761904761905-1.06190476190476
4996.7109.761904761905-13.0619047619048
50101109.761904761905-8.76190476190476
51116.9109.7619047619057.13809523809524
52105.8109.761904761905-3.96190476190477
5399109.761904761905-10.7619047619048
54129.4109.76190476190519.6380952380952
5583109.761904761905-26.7619047619048
5688.9109.761904761905-20.8619047619048
57115.9109.7619047619056.13809523809524
58104.2109.761904761905-5.56190476190476
59113.4109.7619047619053.63809523809524
60112.2109.7619047619052.43809523809524
61100.8109.761904761905-8.96190476190477
62107.3109.761904761905-2.46190476190477
63126.6109.76190476190516.8380952380952
64102.9109.761904761905-6.86190476190476
65117.9109.7619047619058.13809523809524
66128.8109.76190476190519.0380952380952
6787.5109.761904761905-22.2619047619048
6893.8109.761904761905-15.9619047619048
69122.7109.76190476190512.9380952380952
70126.2109.76190476190516.4380952380952
71124.6109.76190476190514.8380952380952
72116.7109.7619047619056.93809523809524
73115.2109.7619047619055.43809523809524
74111.1109.7619047619051.33809523809523
75129.9109.76190476190520.1380952380952
76113.3109.7619047619053.53809523809523
77118.5109.7619047619058.73809523809524
78133.5109.76190476190523.7380952380952
79102.1109.761904761905-7.66190476190477
80102.4109.761904761905-7.36190476190476