Multiple Linear Regression - Estimated Regression Equation
Intention_to_Use[t] = -1.14642 + 0.39772Relative_Advantage[t] + 0.110317Perceived_Usefulness[t] + 0.109761Perceived_Ease_of_Use[t] -0.0274549Information_Quality[t] + 0.106012System_Quality[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0		2-tail p-value1-tail p-value
(Intercept)-1.146 0.8022-1.4290e+00 0.1548 0.07738
Relative_Advantage+0.3977 0.05857+6.7910e+00 1.718e-10 8.589e-11
Perceived_Usefulness+0.1103 0.06063+1.8190e+00 0.07058 0.03529
Perceived_Ease_of_Use+0.1098 0.05536+1.9830e+00 0.04898 0.02449
Information_Quality-0.02746 0.0609-4.5080e-01 0.6527 0.3263
System_Quality+0.106 0.02925+3.6240e+00 0.0003811 0.0001906


Multiple Linear Regression - Regression Statistics
Multiple R 0.7282
R-squared 0.5302
Adjusted R-squared 0.5167
F-TEST (value) 39.06
F-TEST (DF numerator)5
F-TEST (DF denominator)173
p-value 0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation 1.365
Sum Squared Residuals 322.3


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 8.271 1.729
2 8 7.463 0.537
3 8 7.132 0.868
4 9 9.47-0.4698
5 5 6.658-1.658
6 10 9.853 0.1466
7 8 8.067-0.06724
8 9 9.135-0.135
9 8 5.878 2.122
10 7 8.193-1.193
11 10 8.721 1.279
12 10 7.033 2.967
13 9 7.605 1.395
14 4 6.145-2.145
15 4 6.434-2.434
16 8 7.367 0.6329
17 9 9.683-0.6827
18 10 7.929 2.071
19 8 8.105-0.1045
20 5 6.432-1.432
21 10 7.933 2.067
22 8 8.762-0.7622
23 7 7.656-0.6562
24 8 8.273-0.2729
25 8 9.387-1.387
26 9 6.266 2.734
27 8 8.407-0.4069
28 6 7.066-1.066
29 8 8.267-0.2671
30 8 7.397 0.6031
31 5 7.245-2.245
32 9 8.296 0.7041
33 8 8.143-0.1432
34 8 6.034 1.966
35 8 8.644-0.6443
36 6 5.486 0.5137
37 6 6.22-0.2199
38 9 7.466 1.534
39 8 7.127 0.8734
40 9 9.081-0.08107
41 10 7.773 2.227
42 8 7.828 0.1722
43 8 7.844 0.1563
44 7 7.12-0.1198
45 7 6.798 0.2016
46 10 9.277 0.7233
47 8 6.059 1.941
48 7 6.032 0.9684
49 10 7.373 2.627
50 7 8.005-1.005
51 7 5.568 1.432
52 9 8.637 0.3633
53 9 10.19-1.195
54 8 7.125 0.8749
55 6 7.336-1.336
56 8 7.222 0.7776
57 9 7.294 1.706
58 2 3.517-1.517
59 6 5.719 0.2806
60 8 7.371 0.6286
61 8 8.381-0.381
62 7 8.102-1.102
63 8 7.511 0.489
64 6 5.452 0.5481
65 10 7.653 2.347
66 10 8.132 1.868
67 10 7.573 2.427
68 8 7.227 0.7726
69 8 8.148-0.1482
70 7 7.663-0.6631
71 10 8.817 1.183
72 5 6.854-1.854
73 3 3.193-0.193
74 2 3.885-1.885
75 3 4.608-1.608
76 4 5.964-1.964
77 2 3.832-1.832
78 6 5.644 0.3564
79 8 8.139-0.1394
80 8 6.97 1.03
81 5 5.874-0.8738
82 10 8.906 1.094
83 9 9.76-0.7597
84 8 9.866-1.866
85 9 8.969 0.03075
86 8 6.541 1.459
87 5 5.969-0.9686
88 7 7.274-0.2736
89 9 9.78-0.7797
90 8 8.451-0.4505
91 4 7.782-3.782
92 7 6.43 0.57
93 8 8.909-0.9089
94 7 7.55-0.5503
95 7 6.921 0.07882
96 9 7.706 1.294
97 6 6.406-0.4062
98 7 7.836-0.836
99 4 4.719-0.7195
100 6 6.208-0.2075
101 10 6.485 3.515
102 9 8.258 0.7415
103 10 9.964 0.03632
104 8 7.364 0.6361
105 4 5.766-1.766
106 8 9.795-1.795
107 5 6.946-1.946
108 8 7.934 0.06617
109 9 8.335 0.6647
110 8 7.6 0.3997
111 4 7.759-3.759
112 8 6.369 1.631
113 10 7.792 2.208
114 6 6.268-0.2684
115 7 6.216 0.7838
116 10 8.722 1.278
117 9 9.355-0.3546
118 8 8.135-0.1346
119 3 6.225-3.225
120 8 6.798 1.202
121 7 7.368-0.3683
122 7 7.248-0.2484
123 8 6.422 1.578
124 8 8.198-0.1981
125 7 7.506-0.5055
126 7 5.952 1.048
127 9 10.53-1.526
128 9 8.846 0.1535
129 9 7.273 1.727
130 4 5.19-1.19
131 6 6.742-0.7424
132 6 5.515 0.4851
133 6 4.792 1.208
134 8 8.183-0.1831
135 3 4.349-1.349
136 8 6.64 1.36
137 8 8.082-0.08184
138 6 4.898 1.102
139 10 9.386 0.6142
140 2 4.761-2.761
141 9 8.04 0.9602
142 6 5.931 0.06918
143 6 8.562-2.562
144 5 4.864 0.1357
145 4 5.088-1.088
146 7 6.614 0.3856
147 5 6.022-1.022
148 8 8.699-0.6986
149 6 7.493-1.493
150 9 7.468 1.532
151 6 6.038-0.0385
152 4 5.34-1.34
153 7 8.088-1.088
154 2 4.1-2.1
155 8 9.115-1.115
156 9 8.332 0.6679
157 6 6.106-0.1058
158 5 4.453 0.5475
159 7 7.286-0.286
160 8 6.739 1.261
161 4 5.999-1.999
162 9 6.596 2.404
163 9 9.79-0.7898
164 9 5.466 3.534
165 7 6.692 0.308
166 5 6.877-1.877
167 7 7.383-0.3832
168 9 10.07-1.073
169 8 6.128 1.872
170 6 5.874 0.1255
171 9 8.426 0.5743
172 8 7.663 0.3373
173 7 7.653-0.6535
174 7 7.494-0.4942
175 7 7.359-0.3592
176 8 7.097 0.9029
177 10 8.513 1.487
178 6 7.693-1.693
179 6 7.455-1.455


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
9 0.6959 0.6082 0.3041
10 0.5686 0.8627 0.4314
11 0.4493 0.8987 0.5507
12 0.6924 0.6152 0.3076
13 0.6134 0.7733 0.3866
14 0.9122 0.1757 0.08784
15 0.9356 0.1288 0.06442
16 0.9227 0.1546 0.0773
17 0.901 0.1981 0.09904
18 0.8776 0.2448 0.1224
19 0.8414 0.3172 0.1586
20 0.8565 0.2871 0.1435
21 0.9 0.2 0.1
22 0.8987 0.2026 0.1013
23 0.8684 0.2631 0.1316
24 0.8294 0.3413 0.1706
25 0.834 0.3319 0.166
26 0.9155 0.169 0.08449
27 0.8955 0.209 0.1045
28 0.8879 0.2243 0.1121
29 0.8577 0.2846 0.1423
30 0.822 0.3559 0.178
31 0.8544 0.2913 0.1456
32 0.8234 0.3531 0.1766
33 0.7874 0.4251 0.2126
34 0.8229 0.3543 0.1771
35 0.7943 0.4114 0.2057
36 0.7563 0.4873 0.2437
37 0.7195 0.561 0.2805
38 0.7345 0.5311 0.2656
39 0.7011 0.5977 0.2989
40 0.6526 0.6948 0.3474
41 0.7104 0.5792 0.2896
42 0.6641 0.6717 0.3359
43 0.6172 0.7656 0.3828
44 0.5663 0.8674 0.4337
45 0.5155 0.9689 0.4845
46 0.4783 0.9565 0.5217
47 0.4943 0.9886 0.5057
48 0.4535 0.9071 0.5465
49 0.5664 0.8672 0.4336
50 0.5475 0.9049 0.4525
51 0.5207 0.9587 0.4793
52 0.4801 0.9603 0.5199
53 0.45 0.9001 0.55
54 0.4124 0.8249 0.5876
55 0.4185 0.837 0.5815
56 0.3827 0.7653 0.6173
57 0.386 0.7719 0.614
58 0.4531 0.9061 0.5469
59 0.4089 0.8178 0.5911
60 0.369 0.738 0.631
61 0.3273 0.6547 0.6726
62 0.3332 0.6664 0.6668
63 0.2973 0.5946 0.7027
64 0.2616 0.5231 0.7384
65 0.3346 0.6692 0.6654
66 0.3723 0.7447 0.6277
67 0.4601 0.9202 0.5399
68 0.4268 0.8535 0.5732
69 0.3862 0.7725 0.6138
70 0.3598 0.7195 0.6402
71 0.3481 0.6962 0.6519
72 0.403 0.8059 0.597
73 0.382 0.7641 0.618
74 0.4407 0.8814 0.5593
75 0.4606 0.9213 0.5394
76 0.5107 0.9785 0.4893
77 0.5401 0.9198 0.4599
78 0.4994 0.9988 0.5006
79 0.4572 0.9144 0.5428
80 0.4359 0.8717 0.5641
81 0.412 0.8241 0.588
82 0.3979 0.7957 0.6021
83 0.374 0.748 0.626
84 0.4128 0.8255 0.5872
85 0.3717 0.7435 0.6283
86 0.3753 0.7506 0.6247
87 0.3541 0.7081 0.6459
88 0.3167 0.6333 0.6833
89 0.2907 0.5814 0.7093
90 0.2588 0.5176 0.7412
91 0.5239 0.9522 0.4761
92 0.4906 0.9811 0.5094
93 0.4662 0.9323 0.5338
94 0.4291 0.8582 0.5709
95 0.3872 0.7744 0.6128
96 0.3834 0.7669 0.6166
97 0.3449 0.6899 0.6551
98 0.3199 0.6399 0.6801
99 0.2927 0.5854 0.7073
100 0.2567 0.5134 0.7433
101 0.477 0.954 0.523
102 0.4482 0.8964 0.5518
103 0.4054 0.8108 0.5946
104 0.373 0.7461 0.627
105 0.4018 0.8036 0.5982
106 0.4246 0.8491 0.5754
107 0.4626 0.9251 0.5374
108 0.4186 0.8373 0.5814
109 0.3872 0.7743 0.6128
110 0.3495 0.699 0.6505
111 0.628 0.744 0.372
112 0.6458 0.7083 0.3542
113 0.7069 0.5863 0.2931
114 0.6668 0.6663 0.3332
115 0.6407 0.7186 0.3593
116 0.6441 0.7119 0.3559
117 0.6015 0.797 0.3985
118 0.556 0.8879 0.444
119 0.7492 0.5015 0.2508
120 0.745 0.5099 0.255
121 0.7076 0.5848 0.2924
122 0.6658 0.6683 0.3342
123 0.6832 0.6335 0.3168
124 0.6392 0.7215 0.3608
125 0.5977 0.8046 0.4023
126 0.5762 0.8475 0.4238
127 0.5773 0.8454 0.4227
128 0.5288 0.9424 0.4712
129 0.5799 0.8401 0.4201
130 0.583 0.8341 0.417
131 0.5451 0.9097 0.4549
132 0.502 0.9959 0.498
133 0.506 0.9881 0.494
134 0.4577 0.9154 0.5423
135 0.4796 0.9593 0.5204
136 0.481 0.962 0.519
137 0.4287 0.8574 0.5713
138 0.4268 0.8536 0.5732
139 0.4091 0.8182 0.5909
140 0.6097 0.7807 0.3903
141 0.6024 0.7951 0.3976
142 0.5485 0.9029 0.4515
143 0.6609 0.6782 0.3391
144 0.6066 0.7867 0.3934
145 0.5614 0.8773 0.4386
146 0.5137 0.9725 0.4863
147 0.5103 0.9795 0.4897
148 0.4521 0.9042 0.5479
149 0.4981 0.9963 0.5019
150 0.6039 0.7921 0.3961
151 0.5418 0.9165 0.4582
152 0.5227 0.9545 0.4773
153 0.471 0.942 0.529
154 0.5492 0.9016 0.4508
155 0.4847 0.9694 0.5153
156 0.4739 0.9477 0.5261
157 0.4066 0.8131 0.5934
158 0.3876 0.7752 0.6124
159 0.3157 0.6314 0.6843
160 0.2907 0.5814 0.7093
161 0.4557 0.9115 0.5443
162 0.5183 0.9634 0.4817
163 0.49 0.98 0.51
164 0.6275 0.7449 0.3725
165 0.5435 0.9129 0.4565
166 0.6724 0.6552 0.3276
167 0.5583 0.8833 0.4417
168 0.4495 0.8989 0.5505
169 0.9515 0.09707 0.04853
170 0.928 0.1441 0.07205


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 level10.00617284OK


Ramsey RESET F-Test for powers (2 and 3) of fitted values
> reset_test_fitted
	RESET test
data:  mylm
RESET = 7.312, df1 = 2, df2 = 171, p-value = 0.0008974
Ramsey RESET F-Test for powers (2 and 3) of regressors
> reset_test_regressors
	RESET test
data:  mylm
RESET = 1.5219, df1 = 10, df2 = 163, p-value = 0.1357
Ramsey RESET F-Test for powers (2 and 3) of principal components
> reset_test_principal_components
	RESET test
data:  mylm
RESET = 5.2407, df1 = 2, df2 = 171, p-value = 0.006181


Variance Inflation Factors (Multicollinearity)
> vif
   Relative_Advantage  Perceived_Usefulness Perceived_Ease_of_Use 
             1.420090              1.836909              2.405546 
  Information_Quality        System_Quality 
             2.670764              1.727432