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 | |||||
Variable | Parameter | S.D. | T-STAT H0: parameter = 0 | 2-tail p-value | 1-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 | |
Description | Link |
Histogram | Compute |
Central Tendency | Compute |
QQ Plot | Compute |
Kernel Density Plot | Compute |
Skewness/Kurtosis Test | Compute |
Skewness-Kurtosis Plot | Compute |
Harrell-Davis Plot | Compute |
Bootstrap Plot -- Central Tendency | Compute |
Blocked Bootstrap Plot -- Central Tendency | Compute |
(Partial) Autocorrelation Plot | Compute |
Spectral Analysis | Compute |
Tukey lambda PPCC Plot | Compute |
Box-Cox Normality Plot | Compute |
Summary Statistics | Compute |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation 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-values | Alternative Hypothesis | ||
breakpoint index | greater | 2-sided | less |
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 tests | OK/NOK |
1% type I error level | 0 | 0 | OK |
5% type I error level | 0 | 0 | OK |
10% type I error level | 1 | 0.00617284 | OK |
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 |