Multiple Linear Regression - Estimated Regression Equation
Intention_to_Use[t] = -1.16763 + 0.29635Relative_Advantage[t] + 0.0433076Perceived_Usefulness[t] + 0.138004Perceived_Ease_of_Use[t] + 0.03762Information_Quality[t] + 0.0837955System_Quality[t] + 1.01256groupB[t] + 0.149995genderB[t] + 0.235965M1[t] -0.245879M2[t] -0.753034M3[t] -0.304566M4[t] -0.335417M5[t] + 0.780254M6[t] -0.603804M7[t] + 0.0992273M8[t] + 0.265399M9[t] -0.876325M10[t] -0.821279M11[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0		2-tail p-value1-tail p-value
(Intercept)-1.168 0.8669-1.3470e+00 0.1799 0.08997
Relative_Advantage+0.2964 0.0603+4.9150e+00 2.181e-06 1.09e-06
Perceived_Usefulness+0.04331 0.05899+7.3410e-01 0.464 0.232
Perceived_Ease_of_Use+0.138 0.0533+2.5890e+00 0.01051 0.005257
Information_Quality+0.03762 0.05881+6.3960e-01 0.5233 0.2617
System_Quality+0.0838 0.02899+2.8910e+00 0.004376 0.002188
groupB+1.013 0.2432+4.1630e+00 5.109e-05 2.554e-05
genderB+0.15 0.2054+7.3040e-01 0.4662 0.2331
M1+0.236 0.4802+4.9140e-01 0.6238 0.3119
M2-0.2459 0.4815-5.1060e-01 0.6103 0.3052
M3-0.753 0.4804-1.5680e+00 0.119 0.05948
M4-0.3046 0.4794-6.3530e-01 0.5262 0.2631
M5-0.3354 0.482-6.9580e-01 0.4876 0.2438
M6+0.7802 0.4858+1.6060e+00 0.1102 0.05512
M7-0.6038 0.4849-1.2450e+00 0.2149 0.1075
M8+0.09923 0.4777+2.0770e-01 0.8357 0.4179
M9+0.2654 0.478+5.5530e-01 0.5795 0.2897
M10-0.8763 0.4806-1.8230e+00 0.07011 0.03505
M11-0.8213 0.4828-1.7010e+00 0.09084 0.04542


Multiple Linear Regression - Regression Statistics
Multiple R 0.7885
R-squared 0.6218
Adjusted R-squared 0.5792
F-TEST (value) 14.61
F-TEST (DF numerator)18
F-TEST (DF denominator)160
p-value 0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation 1.273
Sum Squared Residuals 259.5


Menu of Residual Diagnostics
DescriptionLink
HistogramCompute
Central TendencyCompute
QQ PlotCompute
Kernel Density PlotCompute
Skewness/Kurtosis TestCompute
Skewness-Kurtosis PlotCompute
Harrell-Davis PlotCompute
Bootstrap Plot -- Central TendencyCompute
Blocked Bootstrap Plot -- Central TendencyCompute
(Partial) Autocorrelation PlotCompute
Spectral AnalysisCompute
Tukey lambda PPCC PlotCompute
Box-Cox Normality PlotCompute
Summary StatisticsCompute


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast		Residuals
Prediction Error
1 10 8.664 1.336
2 8 8.089-0.08878
3 8 6.877 1.123
4 9 9.25-0.2503
5 5 6.808-1.808
6 10 11.06-1.057
7 8 8.138-0.138
8 9 9.698-0.6976
9 8 6.456 1.544
10 7 7.653-0.6532
11 10 8.11 1.89
12 10 7.371 2.629
13 9 8.229 0.7709
14 4 6.231-2.231
15 4 6.449-2.449
16 8 7.784 0.2161
17 9 9.628-0.628
18 10 8.698 1.302
19 8 7.565 0.4347
20 5 6.944-1.944
21 10 8.749 1.251
22 8 7.88 0.1202
23 7 7.349-0.3491
24 8 8.725-0.7245
25 8 9.933-1.933
26 9 6.628 2.372
27 8 7.886 0.1141
28 6 7.369-1.369
29 8 8.222-0.2225
30 8 8.24-0.2398
31 5 6.361-1.361
32 9 8.941 0.05864
33 8 8.559-0.5595
34 8 6.055 1.945
35 8 8.011-0.01077
36 6 6.081-0.08093
37 6 7.008-1.008
38 9 7.931 1.069
39 8 6.993 1.007
40 9 9.382-0.3824
41 10 8.063 1.937
42 8 7.941 0.05896
43 8 7.086 0.9143
44 7 7.491-0.4908
45 7 7.521-0.5214
46 10 8.266 1.734
47 8 6.092 1.908
48 7 6.549 0.4507
49 10 7.998 2.002
50 7 8.287-1.287
51 7 5.281 1.719
52 9 8.622 0.3782
53 9 10.05-1.046
54 8 8.17-0.1697
55 6 7.143-1.143
56 8 7.942 0.05811
57 9 8.116 0.8844
58 2 2.856-0.8559
59 6 5.606 0.3938
60 8 8.048-0.04803
61 8 8.257-0.2571
62 7 7.008-0.007653
63 8 6.978 1.022
64 6 6.125-0.1252
65 10 7.649 2.351
66 10 9.313 0.6869
67 10 7.336 2.664
68 8 7.518 0.4818
69 8 8.748-0.748
70 7 7.384-0.3843
71 10 8.503 1.497
72 5 6.325-1.325
73 3 2.992 0.008029
74 2 3.438-1.438
75 3 3.682-0.6819
76 4 5.562-1.562
77 2 3.305-1.305
78 6 5.887 0.1131
79 8 7.925 0.07545
80 8 7.647 0.3533
81 5 5.68-0.6795
82 10 8.716 1.284
83 9 9.345-0.345
84 8 10.25-2.25
85 9 9.56-0.5596
86 8 7.058 0.9422
87 5 5.647-0.647
88 7 7.559-0.5586
89 9 9.685-0.6848
90 8 9.47-1.47
91 4 7.504-3.504
92 7 6.848 0.1517
93 8 9.432-1.432
94 7 6.772 0.2282
95 7 6.738 0.262
96 9 8.062 0.9379
97 6 6.851-0.851
98 7 7.826-0.8264
99 4 4.795-0.7949
100 6 6.531-0.5309
101 10 6.875 3.125
102 9 9.306-0.3062
103 10 9.716 0.2837
104 8 7.889 0.1112
105 4 5.88-1.88
106 8 9.133-1.133
107 5 6.703-1.703
108 8 7.395 0.6054
109 9 7.868 1.132
110 8 7.751 0.2493
111 4 7.749-3.749
112 8 6.811 1.189
113 10 8.282 1.718
114 6 7.292-1.292
115 7 6.114 0.8864
116 10 8.991 1.009
117 9 9.738-0.7384
118 8 7.824 0.1757
119 3 5.091-2.091
120 8 7.314 0.6863
121 7 8.098-1.098
122 7 7.239-0.2391
123 8 6.141 1.859
124 8 8.353-0.3527
125 7 7.688-0.6878
126 7 6.56 0.4395
127 9 9.907-0.9072
128 9 8.508 0.4915
129 9 8.186 0.8138
130 4 4.571-0.5714
131 6 6.549-0.5494
132 6 6.291-0.2906
133 6 4.726 1.274
134 8 8.158-0.1575
135 3 3.85-0.8498
136 8 6.024 1.976
137 8 7.189 0.8108
138 6 5.504 0.4958
139 10 8.91 1.09
140 2 4.46-2.46
141 9 7.744 1.256
142 6 4.951 1.049
143 6 7.219-1.219
144 5 4.541 0.4586
145 4 4.993-0.9929
146 7 6.56 0.4397
147 5 5.248-0.2478
148 8 7.571 0.4286
149 6 6.528-0.5283
150 9 7.679 1.321
151 6 5.886 0.1144
152 4 4.996-0.9964
153 7 7.622-0.6221
154 2 3.009-1.009
155 8 8.502-0.5017
156 9 8.609 0.3912
157 6 6.797-0.7971
158 5 4.749 0.2515
159 7 6.071 0.9292
160 8 7.295 0.7051
161 4 6.237-2.237
162 9 7.19 1.81
163 9 9.217-0.217
164 9 5.619 3.381
165 7 6.255 0.745
166 5 6.614-1.614
167 7 6.019 0.9808
168 9 10.44-1.44
169 8 7.026 0.9735
170 6 5.048 0.952
171 9 7.355 1.645
172 8 7.762 0.2378
173 7 7.794-0.7941
174 7 8.693-1.693
175 7 6.194 0.8063
176 8 7.508 0.492
177 10 9.314 0.6863
178 6 6.315-0.3147
179 6 6.163-0.1634


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
22 0.6227 0.7546 0.3773
23 0.8852 0.2296 0.1148
24 0.961 0.07806 0.03903
25 0.9715 0.05703 0.02852
26 0.973 0.05409 0.02705
27 0.9606 0.07873 0.03936
28 0.9493 0.1015 0.05075
29 0.9232 0.1536 0.0768
30 0.9269 0.1463 0.07313
31 0.8987 0.2025 0.1013
32 0.8676 0.2649 0.1324
33 0.9377 0.1246 0.06229
34 0.9472 0.1055 0.05276
35 0.9419 0.1163 0.05813
36 0.9421 0.1158 0.05792
37 0.9317 0.1366 0.06828
38 0.9242 0.1517 0.07583
39 0.9177 0.1646 0.08229
40 0.8926 0.2148 0.1074
41 0.929 0.1421 0.07105
42 0.9093 0.1813 0.09065
43 0.8887 0.2226 0.1113
44 0.8717 0.2566 0.1283
45 0.8598 0.2805 0.1402
46 0.8619 0.2763 0.1381
47 0.865 0.2699 0.135
48 0.8363 0.3273 0.1637
49 0.8703 0.2594 0.1297
50 0.8711 0.2577 0.1289
51 0.8788 0.2424 0.1212
52 0.8626 0.2749 0.1374
53 0.8413 0.3174 0.1587
54 0.8094 0.3811 0.1906
55 0.7939 0.4121 0.2061
56 0.7661 0.4679 0.2339
57 0.7366 0.5268 0.2634
58 0.7122 0.5755 0.2878
59 0.6773 0.6455 0.3227
60 0.6332 0.7336 0.3668
61 0.5955 0.8091 0.4045
62 0.5455 0.909 0.4545
63 0.5241 0.9519 0.4759
64 0.4744 0.9487 0.5256
65 0.594 0.812 0.406
66 0.5568 0.8864 0.4432
67 0.7038 0.5924 0.2962
68 0.6728 0.6544 0.3272
69 0.6503 0.6993 0.3497
70 0.6135 0.773 0.3865
71 0.6193 0.7615 0.3807
72 0.6084 0.7832 0.3916
73 0.5641 0.8718 0.4359
74 0.5534 0.8932 0.4466
75 0.5064 0.9873 0.4936
76 0.519 0.9619 0.481
77 0.4994 0.9989 0.5006
78 0.4568 0.9135 0.5432
79 0.4131 0.8262 0.5869
80 0.3735 0.7469 0.6265
81 0.3335 0.6669 0.6665
82 0.3409 0.6818 0.6591
83 0.3182 0.6364 0.6818
84 0.4104 0.8208 0.5896
85 0.3759 0.7518 0.6241
86 0.3533 0.7065 0.6467
87 0.3304 0.6607 0.6696
88 0.2988 0.5975 0.7012
89 0.2682 0.5365 0.7318
90 0.2862 0.5724 0.7138
91 0.6046 0.7907 0.3954
92 0.5604 0.8792 0.4396
93 0.5559 0.8881 0.4441
94 0.5447 0.9107 0.4553
95 0.517 0.966 0.483
96 0.5014 0.9973 0.4986
97 0.4796 0.9592 0.5204
98 0.4529 0.9057 0.5471
99 0.4246 0.8493 0.5754
100 0.3939 0.7878 0.6061
101 0.6615 0.677 0.3385
102 0.6189 0.7622 0.3811
103 0.5868 0.8264 0.4132
104 0.5428 0.9144 0.4572
105 0.6012 0.7976 0.3988
106 0.5737 0.8526 0.4263
107 0.5997 0.8007 0.4003
108 0.5798 0.8404 0.4202
109 0.5733 0.8535 0.4267
110 0.5277 0.9446 0.4723
111 0.8733 0.2533 0.1267
112 0.8672 0.2657 0.1328
113 0.8973 0.2054 0.1027
114 0.8884 0.2233 0.1116
115 0.8818 0.2364 0.1182
116 0.8797 0.2406 0.1203
117 0.8692 0.2617 0.1308
118 0.8456 0.3089 0.1544
119 0.8607 0.2786 0.1393
120 0.8621 0.2758 0.1379
121 0.8495 0.301 0.1505
122 0.816 0.3679 0.184
123 0.9099 0.1802 0.09012
124 0.897 0.2059 0.103
125 0.8824 0.2351 0.1176
126 0.8648 0.2704 0.1352
127 0.8644 0.2712 0.1356
128 0.8407 0.3187 0.1593
129 0.8524 0.2952 0.1476
130 0.8336 0.3328 0.1664
131 0.8053 0.3893 0.1947
132 0.7615 0.4769 0.2385
133 0.778 0.4439 0.222
134 0.7338 0.5323 0.2662
135 0.7202 0.5597 0.2798
136 0.7692 0.4616 0.2308
137 0.7483 0.5034 0.2517
138 0.703 0.594 0.297
139 0.7357 0.5287 0.2643
140 0.9187 0.1626 0.08131
141 0.895 0.21 0.105
142 0.899 0.2019 0.101
143 0.8994 0.2011 0.1006
144 0.9149 0.1701 0.08506
145 0.8835 0.233 0.1165
146 0.8404 0.3192 0.1596
147 0.9058 0.1885 0.09424
148 0.878 0.2441 0.122
149 0.823 0.3539 0.1769
150 0.831 0.338 0.169
151 0.783 0.4341 0.217
152 0.9151 0.1697 0.08487
153 0.9412 0.1176 0.05879
154 0.9363 0.1274 0.06372
155 0.8766 0.2469 0.1234
156 0.9706 0.05872 0.02936
157 0.9342 0.1316 0.0658


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level0 0OK
5% type I error level00OK
10% type I error level50.0367647OK


Ramsey RESET F-Test for powers (2 and 3) of fitted values
> reset_test_fitted
	RESET test
data:  mylm
RESET = 7.9337, df1 = 2, df2 = 158, p-value = 0.0005208
Ramsey RESET F-Test for powers (2 and 3) of regressors
> reset_test_regressors
	RESET test
data:  mylm
RESET = 0.25649, df1 = 36, df2 = 124, p-value = 1
Ramsey RESET F-Test for powers (2 and 3) of principal components
> reset_test_principal_components
	RESET test
data:  mylm
RESET = 3.9938, df1 = 2, df2 = 158, p-value = 0.02032


Variance Inflation Factors (Multicollinearity)
> vif
   Relative_Advantage  Perceived_Usefulness Perceived_Ease_of_Use 
             1.728855              1.997349              2.562090 
  Information_Quality        System_Quality                groupB 
             2.861301              1.948289              1.297932 
              genderB                    M1                    M2 
             1.163430              1.954269              1.964993 
                   M3                    M4                    M5 
             1.955686              1.947958              1.969230 
                   M6                    M7                    M8 
             2.000278              1.992922              1.933700 
                   M9                   M10                   M11 
             1.936058              1.957378              1.975002