Multiple Linear Regression - Estimated Regression Equation
Intention_to_Use[t] = -1.1124 + 0.326279Relative_Advantage[t] + 0.0973626Perceived_Usefulness[t] + 0.104497Perceived_Ease_of_Use[t] + 0.00200567Information_Quality[t] + 0.0908982System_Quality[t] + 0.875308groupB[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0		2-tail p-value1-tail p-value
(Intercept)-1.112 0.7767-1.4320e+00 0.1539 0.07694
Relative_Advantage+0.3263 0.06018+5.4220e+00 1.97e-07 9.852e-08
Perceived_Usefulness+0.09736 0.05882+1.6550e+00 0.09967 0.04984
Perceived_Ease_of_Use+0.1045 0.05362+1.9490e+00 0.05292 0.02646
Information_Quality+0.002006 0.05954+3.3680e-02 0.9732 0.4866
System_Quality+0.0909 0.02864+3.1740e+00 0.001783 0.0008913
groupB+0.8753 0.2469+3.5450e+00 0.000505 0.0002525


Multiple Linear Regression - Regression Statistics
Multiple R 0.7498
R-squared 0.5622
Adjusted R-squared 0.547
F-TEST (value) 36.82
F-TEST (DF numerator)6
F-TEST (DF denominator)172
p-value 0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation 1.321
Sum Squared Residuals 300.3


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 8.359 1.641
2 8 7.77 0.2303
3 8 7.386 0.6144
4 9 9.439-0.4389
5 5 6.922-1.922
6 10 9.868 0.132
7 8 8.306-0.3061
8 9 9.216-0.2161
9 8 6.099 1.901
10 7 8.368-1.368
11 10 8.744 1.256
12 10 7.246 2.754
13 9 7.791 1.209
14 4 6.382-2.382
15 4 6.811-2.811
16 8 7.671 0.3285
17 9 9.69-0.6904
18 10 7.916 2.084
19 8 8.195-0.1948
20 5 6.719-1.719
21 10 8.144 1.856
22 8 8.752-0.752
23 7 7.854-0.8539
24 8 8.421-0.4214
25 8 9.441-1.441
26 9 6.667 2.333
27 8 8.478-0.4781
28 6 7.292-1.292
29 8 8.323-0.3227
30 8 7.478 0.5217
31 5 6.665-1.665
32 9 8.521 0.4791
33 8 8.234-0.2336
34 8 6.512 1.488
35 8 8.71-0.7104
36 6 5.972 0.028
37 6 6.544-0.5441
38 9 7.71 1.29
39 8 7.418 0.5815
40 9 9.207-0.207
41 10 8.018 1.982
42 8 7.138 0.8615
43 8 7.839 0.1606
44 7 7.251-0.2511
45 7 7.066-0.06567
46 10 9.13 0.8704
47 8 6.457 1.543
48 7 6.372 0.6282
49 10 7.524 2.477
50 7 8.145-1.145
51 7 5.977 1.023
52 9 8.684 0.3157
53 9 10.13-1.132
54 8 7.326 0.6738
55 6 7.522-1.522
56 8 7.517 0.4833
57 9 7.546 1.454
58 2 3.397-1.397
59 6 6.173-0.1727
60 8 7.678 0.3221
61 8 7.697 0.303
62 7 7.349-0.3495
63 8 7.594 0.4062
64 6 6.002-0.002088
65 10 7.808 2.192
66 10 8.28 1.72
67 10 7.755 2.245
68 8 7.404 0.5965
69 8 8.237-0.2374
70 7 7.913-0.9133
71 10 8.995 1.005
72 5 6.267-1.267
73 3 2.857 0.1427
74 2 3.584-1.584
75 3 4.218-1.218
76 4 5.557-1.557
77 2 3.543-1.543
78 6 5.148 0.8517
79 8 8.332-0.3325
80 8 7.338 0.6619
81 5 5.455-0.4554
82 10 9.008 0.9915
83 9 9.804-0.8036
84 8 9.895-1.895
85 9 9.042-0.04243
86 8 6.87 1.13
87 5 6.326-1.326
88 7 7.499-0.4991
89 9 9.774-0.7744
90 8 8.546-0.5458
91 4 7.916-3.916
92 7 6.558 0.4421
93 8 8.937-0.9372
94 7 7.651-0.6505
95 7 7.169-0.169
96 9 7.883 1.117
97 6 6.624-0.6236
98 7 7.926-0.9259
99 4 5.283-1.283
100 6 6.543-0.5427
101 10 6.906 3.094
102 9 8.335 0.6652
103 10 9.965 0.03463
104 8 7.651 0.3493
105 4 5.386-1.386
106 8 9.746-1.746
107 5 7.246-2.246
108 8 7.229 0.7706
109 9 7.594 1.406
110 8 7.76 0.2403
111 4 8.031-4.031
112 8 6.818 1.182
113 10 8.14 1.86
114 6 6.474-0.4736
115 7 6.531 0.4695
116 10 8.73 1.27
117 9 9.338-0.3376
118 8 8.358-0.3582
119 3 5.781-2.781
120 8 7.048 0.9523
121 7 7.632-0.6321
122 7 7.448-0.4475
123 8 6.751 1.249
124 8 8.342-0.3421
125 7 7.764-0.7642
126 7 5.555 1.445
127 9 10.42-1.424
128 9 8.151 0.8488
129 9 7.481 1.519
130 4 4.942-0.9423
131 6 7.084-1.084
132 6 5.935 0.06479
133 6 4.402 1.598
134 8 8.263-0.2626
135 3 4.167-1.167
136 8 6.131 1.869
137 8 7.297 0.7031
138 6 4.492 1.508
139 10 9.354 0.6462
140 2 4.415-2.415
141 9 7.32 1.68
142 6 5.486 0.5136
143 6 7.835-1.835
144 5 4.536 0.4641
145 4 4.651-0.6505
146 7 6.875 0.1253
147 5 5.603-0.6032
148 8 7.863 0.1368
149 6 6.858-0.8579
150 9 6.781 2.219
151 6 6.431-0.4312
152 4 4.882-0.8819
153 7 7.362-0.3623
154 2 3.679-1.679
155 8 9.057-1.057
156 9 8.424 0.5762
157 6 6.458-0.4582
158 5 4.317 0.683
159 7 6.65 0.3497
160 8 7.146 0.8539
161 4 6.374-2.374
162 9 6.096 2.904
163 9 9.742-0.742
164 9 5.163 3.837
165 7 5.999 1.001
166 5 7.134-2.134
167 7 6.861 0.1387
168 9 10.1-1.102
169 8 6.489 1.511
170 6 5.311 0.6893
171 9 7.7 1.3
172 8 7.808 0.1921
173 7 7.827-0.8272
174 7 7.669-0.6688
175 7 6.668 0.3319
176 8 7.36 0.6396
177 10 8.707 1.293
178 6 7.089-1.089
179 6 6.87-0.8698


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
10 0.7453 0.5094 0.2547
11 0.6267 0.7465 0.3733
12 0.8194 0.3613 0.1806
13 0.7518 0.4965 0.2482
14 0.9592 0.08152 0.04076
15 0.9728 0.0545 0.02725
16 0.9656 0.06874 0.03437
17 0.9535 0.09295 0.04648
18 0.9402 0.1197 0.05984
19 0.9178 0.1644 0.08222
20 0.9287 0.1425 0.07126
21 0.9533 0.0933 0.04665
22 0.9527 0.09464 0.04732
23 0.9356 0.1287 0.06437
24 0.9118 0.1764 0.08821
25 0.9156 0.1687 0.08437
26 0.9613 0.07748 0.03874
27 0.9502 0.09958 0.04979
28 0.9469 0.1062 0.0531
29 0.9293 0.1414 0.07072
30 0.9068 0.1864 0.09322
31 0.8873 0.2255 0.1127
32 0.8615 0.2771 0.1385
33 0.829 0.342 0.171
34 0.8477 0.3045 0.1523
35 0.8195 0.361 0.1805
36 0.7829 0.4342 0.2171
37 0.7476 0.5049 0.2524
38 0.7467 0.5065 0.2533
39 0.706 0.5879 0.294
40 0.6573 0.6854 0.3427
41 0.711 0.578 0.289
42 0.7222 0.5556 0.2778
43 0.6768 0.6464 0.3232
44 0.629 0.7419 0.371
45 0.5796 0.8409 0.4204
46 0.5445 0.911 0.4555
47 0.5506 0.8987 0.4494
48 0.505 0.99 0.495
49 0.6131 0.7738 0.3869
50 0.6006 0.7987 0.3994
51 0.5665 0.8671 0.4335
52 0.5231 0.9537 0.4769
53 0.4954 0.9907 0.5046
54 0.4539 0.9078 0.5461
55 0.4688 0.9376 0.5312
56 0.4275 0.855 0.5725
57 0.4246 0.8491 0.5754
58 0.4172 0.8344 0.5828
59 0.3754 0.7509 0.6246
60 0.3326 0.6653 0.6674
61 0.3126 0.6253 0.6874
62 0.2733 0.5465 0.7267
63 0.2393 0.4787 0.7607
64 0.2044 0.4088 0.7956
65 0.2632 0.5265 0.7368
66 0.2903 0.5806 0.7097
67 0.3637 0.7273 0.6363
68 0.3293 0.6586 0.6707
69 0.2929 0.5859 0.7071
70 0.2773 0.5546 0.7227
71 0.262 0.5241 0.738
72 0.2475 0.495 0.7525
73 0.2147 0.4294 0.7853
74 0.2169 0.4338 0.7831
75 0.1992 0.3984 0.8008
76 0.196 0.3921 0.804
77 0.1917 0.3834 0.8083
78 0.1888 0.3776 0.8112
79 0.1636 0.3272 0.8364
80 0.1432 0.2865 0.8568
81 0.1214 0.2428 0.8786
82 0.116 0.232 0.884
83 0.1046 0.2091 0.8954
84 0.1277 0.2555 0.8723
85 0.1064 0.2129 0.8936
86 0.1018 0.2037 0.8982
87 0.1064 0.2128 0.8936
88 0.09089 0.1818 0.9091
89 0.07914 0.1583 0.9209
90 0.06691 0.1338 0.9331
91 0.2683 0.5366 0.7317
92 0.2396 0.4792 0.7604
93 0.2209 0.4418 0.7791
94 0.1972 0.3943 0.8028
95 0.1692 0.3384 0.8308
96 0.1633 0.3265 0.8367
97 0.1443 0.2886 0.8557
98 0.1306 0.2613 0.8694
99 0.1302 0.2605 0.8698
100 0.1116 0.2232 0.8884
101 0.239 0.4779 0.761
102 0.2159 0.4318 0.7841
103 0.185 0.37 0.815
104 0.1599 0.3199 0.8401
105 0.1588 0.3177 0.8412
106 0.1722 0.3445 0.8278
107 0.2206 0.4412 0.7794
108 0.2097 0.4195 0.7903
109 0.2219 0.4439 0.7781
110 0.1915 0.383 0.8085
111 0.5078 0.9844 0.4922
112 0.4977 0.9954 0.5023
113 0.5399 0.9202 0.4601
114 0.4986 0.9971 0.5014
115 0.4607 0.9214 0.5393
116 0.4637 0.9274 0.5363
117 0.4197 0.8394 0.5803
118 0.3767 0.7534 0.6233
119 0.5409 0.9181 0.4591
120 0.5262 0.9476 0.4738
121 0.487 0.9739 0.513
122 0.4437 0.8873 0.5563
123 0.4452 0.8905 0.5548
124 0.3993 0.7986 0.6007
125 0.3632 0.7264 0.6368
126 0.3696 0.7391 0.6304
127 0.3717 0.7434 0.6283
128 0.3431 0.6863 0.6569
129 0.3806 0.7611 0.6194
130 0.376 0.752 0.624
131 0.3509 0.7018 0.6491
132 0.3069 0.6139 0.6931
133 0.3324 0.6648 0.6676
134 0.2881 0.5762 0.7119
135 0.3053 0.6106 0.6947
136 0.3344 0.6687 0.6656
137 0.2955 0.591 0.7045
138 0.3099 0.6199 0.6901
139 0.2885 0.577 0.7115
140 0.4612 0.9224 0.5388
141 0.4883 0.9766 0.5117
142 0.4392 0.8783 0.5608
143 0.5162 0.9677 0.4838
144 0.4615 0.9229 0.5385
145 0.4084 0.8168 0.5916
146 0.3573 0.7147 0.6427
147 0.3483 0.6967 0.6517
148 0.2938 0.5877 0.7062
149 0.3212 0.6424 0.6788
150 0.4571 0.9142 0.5429
151 0.3986 0.7972 0.6014
152 0.3675 0.7351 0.6325
153 0.3108 0.6216 0.6892
154 0.3732 0.7464 0.6268
155 0.313 0.6261 0.687
156 0.3027 0.6055 0.6973
157 0.2471 0.4941 0.7529
158 0.235 0.4701 0.765
159 0.1801 0.3601 0.8199
160 0.1575 0.315 0.8425
161 0.331 0.6619 0.669
162 0.4246 0.8492 0.5754
163 0.418 0.836 0.582
164 0.5472 0.9055 0.4528
165 0.4412 0.8824 0.5588
166 0.7669 0.4662 0.2331
167 0.6566 0.6868 0.3434
168 0.5144 0.9712 0.4856
169 0.9279 0.1442 0.07208


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 level80.05OK


Ramsey RESET F-Test for powers (2 and 3) of fitted values
> reset_test_fitted
	RESET test
data:  mylm
RESET = 5.4471, df1 = 2, df2 = 170, p-value = 0.005094
Ramsey RESET F-Test for powers (2 and 3) of regressors
> reset_test_regressors
	RESET test
data:  mylm
RESET = 0.87893, df1 = 12, df2 = 160, p-value = 0.5696
Ramsey RESET F-Test for powers (2 and 3) of principal components
> reset_test_principal_components
	RESET test
data:  mylm
RESET = 4.1635, df1 = 2, df2 = 170, p-value = 0.01717


Variance Inflation Factors (Multicollinearity)
> vif
   Relative_Advantage  Perceived_Usefulness Perceived_Ease_of_Use 
             1.599420              1.844025              2.407392 
  Information_Quality        System_Quality                groupB 
             2.723810              1.766570              1.242243