Multiple Linear Regression - Estimated Regression Equation |
Intention_to_Use[t] = -1.92814 + 0.2929Relative_Advantage[t] + 0.0853193Perceived_Usefulness[t] + 0.106187Perceived_Ease_of_Use[t] + 0.036988Information_Quality[t] + 0.0709976System_Quality[t] + 1.00629groupB[t] + 0.334666genderB[t] -0.0164075`Intention_to_Use(t-1)`[t] + 0.0247869`Intention_to_Use(t-1s)`[t] -0.040615`Intention_to_Use(t-2s)`[t] -0.0337217`Intention_to_Use(t-3s)`[t] + 0.0618448`Intention_to_Use(t-4s)`[t] -0.0764146`Intention_to_Use(t-5s)`[t] + 0.0791039`Intention_to_Use(t-6s)`[t] + 0.143331`Intention_to_Use(t-7s)`[t] + 0.0545301`Intention_to_Use(t-8s)`[t] -0.0391061`Intention_to_Use(t-9s)`[t] + 0.0400292`Intention_to_Use(t-10s)`[t] -0.0460857`Intention_to_Use(t-11s)`[t] -0.0213416`Intention_to_Use(t-12s)`[t] + e[t] |
Warning: you did not specify the column number of the endogenous series! The first column was selected by default. |
Multiple Linear Regression - Ordinary Least Squares | |||||
Variable | Parameter | S.D. | T-STAT H0: parameter = 0 | 2-tail p-value | 1-tail p-value |
(Intercept) | -1.928 | 1.559 | -1.2370e+00 | 0.2183 | 0.1091 |
Relative_Advantage | +0.2929 | 0.06792 | +4.3120e+00 | 3.123e-05 | 1.561e-05 |
Perceived_Usefulness | +0.08532 | 0.06578 | +1.2970e+00 | 0.1969 | 0.09843 |
Perceived_Ease_of_Use | +0.1062 | 0.06127 | +1.7330e+00 | 0.08541 | 0.0427 |
Information_Quality | +0.03699 | 0.07099 | +5.2100e-01 | 0.6032 | 0.3016 |
System_Quality | +0.071 | 0.03325 | +2.1350e+00 | 0.03457 | 0.01728 |
groupB | +1.006 | 0.2603 | +3.8660e+00 | 0.0001724 | 8.62e-05 |
genderB | +0.3347 | 0.2292 | +1.4600e+00 | 0.1467 | 0.07334 |
`Intention_to_Use(t-1)` | -0.01641 | 0.05706 | -2.8750e-01 | 0.7741 | 0.3871 |
`Intention_to_Use(t-1s)` | +0.02479 | 0.05722 | +4.3320e-01 | 0.6656 | 0.3328 |
`Intention_to_Use(t-2s)` | -0.04061 | 0.06109 | -6.6480e-01 | 0.5073 | 0.2537 |
`Intention_to_Use(t-3s)` | -0.03372 | 0.05876 | -5.7390e-01 | 0.567 | 0.2835 |
`Intention_to_Use(t-4s)` | +0.06184 | 0.05618 | +1.1010e+00 | 0.2729 | 0.1365 |
`Intention_to_Use(t-5s)` | -0.07641 | 0.05654 | -1.3520e+00 | 0.1788 | 0.08941 |
`Intention_to_Use(t-6s)` | +0.0791 | 0.05599 | +1.4130e+00 | 0.1601 | 0.08003 |
`Intention_to_Use(t-7s)` | +0.1433 | 0.0558 | +2.5690e+00 | 0.01131 | 0.005656 |
`Intention_to_Use(t-8s)` | +0.05453 | 0.05583 | +9.7660e-01 | 0.3305 | 0.1653 |
`Intention_to_Use(t-9s)` | -0.03911 | 0.0564 | -6.9340e-01 | 0.4893 | 0.2446 |
`Intention_to_Use(t-10s)` | +0.04003 | 0.05513 | +7.2610e-01 | 0.4691 | 0.2345 |
`Intention_to_Use(t-11s)` | -0.04609 | 0.05511 | -8.3630e-01 | 0.4045 | 0.2022 |
`Intention_to_Use(t-12s)` | -0.02134 | 0.05862 | -3.6400e-01 | 0.7164 | 0.3582 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.7973 |
R-squared | 0.6356 |
Adjusted R-squared | 0.5808 |
F-TEST (value) | 11.6 |
F-TEST (DF numerator) | 20 |
F-TEST (DF denominator) | 133 |
p-value | 0 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 1.272 |
Sum Squared Residuals | 215.3 |
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 | 9 | 6.869 | 2.131 |
2 | 8 | 8.355 | -0.3545 |
3 | 6 | 6.854 | -0.8545 |
4 | 8 | 8.338 | -0.3385 |
5 | 8 | 7.227 | 0.7731 |
6 | 5 | 6.612 | -1.612 |
7 | 9 | 9.292 | -0.2917 |
8 | 8 | 8.423 | -0.4228 |
9 | 8 | 6.307 | 1.693 |
10 | 8 | 8.716 | -0.7164 |
11 | 6 | 5.665 | 0.3354 |
12 | 6 | 6.904 | -0.904 |
13 | 9 | 8.515 | 0.4848 |
14 | 8 | 7.361 | 0.6394 |
15 | 9 | 9.431 | -0.4312 |
16 | 10 | 8.771 | 1.229 |
17 | 8 | 6.77 | 1.23 |
18 | 8 | 7.456 | 0.544 |
19 | 7 | 6.862 | 0.1376 |
20 | 7 | 6.744 | 0.2561 |
21 | 10 | 9.58 | 0.4196 |
22 | 8 | 6.824 | 1.176 |
23 | 7 | 6.554 | 0.4461 |
24 | 10 | 7.914 | 2.086 |
25 | 7 | 8.07 | -1.07 |
26 | 7 | 5.582 | 1.418 |
27 | 9 | 8.603 | 0.3966 |
28 | 9 | 9.958 | -0.9578 |
29 | 8 | 7.792 | 0.2076 |
30 | 6 | 7.967 | -1.967 |
31 | 8 | 7.222 | 0.7777 |
32 | 9 | 7.932 | 1.068 |
33 | 2 | 3.674 | -1.674 |
34 | 6 | 6.106 | -0.1065 |
35 | 8 | 8.263 | -0.263 |
36 | 8 | 8.199 | -0.1986 |
37 | 7 | 7.249 | -0.2492 |
38 | 8 | 7.52 | 0.4802 |
39 | 6 | 6.152 | -0.1518 |
40 | 10 | 8.095 | 1.905 |
41 | 10 | 8.124 | 1.876 |
42 | 10 | 7.453 | 2.547 |
43 | 8 | 7.888 | 0.1116 |
44 | 8 | 8.583 | -0.5832 |
45 | 7 | 7.647 | -0.6469 |
46 | 10 | 8.79 | 1.21 |
47 | 5 | 5.266 | -0.2661 |
48 | 3 | 3.148 | -0.1477 |
49 | 2 | 3.829 | -1.829 |
50 | 3 | 4.144 | -1.144 |
51 | 4 | 5.801 | -1.801 |
52 | 2 | 3.797 | -1.797 |
53 | 6 | 4.96 | 1.04 |
54 | 8 | 9.08 | -1.08 |
55 | 8 | 8.088 | -0.08757 |
56 | 5 | 5.829 | -0.8293 |
57 | 10 | 9.679 | 0.3211 |
58 | 9 | 10.52 | -1.52 |
59 | 8 | 10.01 | -2.01 |
60 | 9 | 9.351 | -0.3508 |
61 | 8 | 6.531 | 1.469 |
62 | 5 | 5.914 | -0.9139 |
63 | 7 | 6.586 | 0.4142 |
64 | 9 | 8.018 | 0.9817 |
65 | 8 | 7.533 | 0.4671 |
66 | 4 | 7.663 | -3.663 |
67 | 7 | 6.375 | 0.6249 |
68 | 8 | 8.423 | -0.4232 |
69 | 7 | 7.669 | -0.6694 |
70 | 7 | 7.303 | -0.3025 |
71 | 9 | 8.316 | 0.6839 |
72 | 6 | 7.351 | -1.351 |
73 | 7 | 8.342 | -1.342 |
74 | 4 | 5.526 | -1.526 |
75 | 6 | 6.851 | -0.8508 |
76 | 10 | 6.986 | 3.014 |
77 | 9 | 8.478 | 0.5217 |
78 | 10 | 10.22 | -0.2167 |
79 | 8 | 7.665 | 0.3347 |
80 | 4 | 5.117 | -1.117 |
81 | 8 | 9.64 | -1.64 |
82 | 5 | 6.366 | -1.366 |
83 | 8 | 7.179 | 0.8207 |
84 | 9 | 8.146 | 0.8539 |
85 | 8 | 8.015 | -0.01538 |
86 | 4 | 7.796 | -3.796 |
87 | 8 | 6.758 | 1.242 |
88 | 10 | 7.793 | 2.207 |
89 | 6 | 6.101 | -0.1009 |
90 | 7 | 7.248 | -0.2476 |
91 | 10 | 9.039 | 0.9608 |
92 | 9 | 9.992 | -0.992 |
93 | 8 | 8.849 | -0.849 |
94 | 3 | 4.69 | -1.69 |
95 | 8 | 7.033 | 0.9673 |
96 | 7 | 7.632 | -0.6323 |
97 | 7 | 7.413 | -0.4129 |
98 | 8 | 6.682 | 1.318 |
99 | 8 | 8.883 | -0.8833 |
100 | 7 | 7.565 | -0.5649 |
101 | 7 | 5.601 | 1.399 |
102 | 9 | 9.822 | -0.8222 |
103 | 9 | 8.237 | 0.7633 |
104 | 9 | 8.336 | 0.6644 |
105 | 4 | 5.53 | -1.53 |
106 | 6 | 6.773 | -0.7729 |
107 | 6 | 6.492 | -0.4917 |
108 | 6 | 3.765 | 2.235 |
109 | 8 | 7.986 | 0.014 |
110 | 3 | 3.947 | -0.9467 |
111 | 8 | 6.563 | 1.437 |
112 | 8 | 7.439 | 0.5606 |
113 | 6 | 4.343 | 1.657 |
114 | 10 | 9.046 | 0.954 |
115 | 2 | 4.397 | -2.397 |
116 | 9 | 8.124 | 0.8764 |
117 | 6 | 5.572 | 0.4277 |
118 | 6 | 7.71 | -1.71 |
119 | 5 | 4.317 | 0.6832 |
120 | 4 | 4.459 | -0.4594 |
121 | 7 | 6.413 | 0.587 |
122 | 5 | 5.292 | -0.2924 |
123 | 8 | 8.066 | -0.06552 |
124 | 6 | 5.992 | 0.008303 |
125 | 9 | 7.219 | 1.781 |
126 | 6 | 6.258 | -0.258 |
127 | 4 | 4.504 | -0.504 |
128 | 7 | 7.844 | -0.8438 |
129 | 2 | 3 | -0.9998 |
130 | 8 | 9.562 | -1.562 |
131 | 9 | 7.974 | 1.026 |
132 | 6 | 6.311 | -0.3107 |
133 | 5 | 4.943 | 0.05662 |
134 | 7 | 6.15 | 0.8504 |
135 | 8 | 7.063 | 0.9365 |
136 | 4 | 5.784 | -1.784 |
137 | 9 | 6.835 | 2.165 |
138 | 9 | 9.006 | -0.005997 |
139 | 9 | 6.071 | 2.929 |
140 | 7 | 5.374 | 1.626 |
141 | 5 | 6.367 | -1.367 |
142 | 7 | 6.924 | 0.07646 |
143 | 9 | 9.495 | -0.4953 |
144 | 8 | 6.582 | 1.418 |
145 | 6 | 5.457 | 0.5428 |
146 | 9 | 8.141 | 0.859 |
147 | 8 | 7.673 | 0.3274 |
148 | 7 | 7.464 | -0.4645 |
149 | 7 | 7.252 | -0.2524 |
150 | 7 | 6.002 | 0.9979 |
151 | 8 | 8.416 | -0.4156 |
152 | 10 | 8.931 | 1.069 |
153 | 6 | 6.688 | -0.6884 |
154 | 6 | 7.084 | -1.084 |
Goldfeld-Quandt test for Heteroskedasticity | |||
p-values | Alternative Hypothesis | ||
breakpoint index | greater | 2-sided | less |
24 | 0.2498 | 0.4996 | 0.7502 |
25 | 0.1648 | 0.3296 | 0.8352 |
26 | 0.1222 | 0.2444 | 0.8778 |
27 | 0.1028 | 0.2056 | 0.8972 |
28 | 0.06003 | 0.1201 | 0.94 |
29 | 0.03432 | 0.06865 | 0.9657 |
30 | 0.03851 | 0.07702 | 0.9615 |
31 | 0.1163 | 0.2326 | 0.8837 |
32 | 0.09017 | 0.1803 | 0.9098 |
33 | 0.08714 | 0.1743 | 0.9129 |
34 | 0.07531 | 0.1506 | 0.9247 |
35 | 0.1007 | 0.2014 | 0.8993 |
36 | 0.07065 | 0.1413 | 0.9293 |
37 | 0.04625 | 0.09249 | 0.9538 |
38 | 0.06963 | 0.1393 | 0.9304 |
39 | 0.05808 | 0.1162 | 0.9419 |
40 | 0.07684 | 0.1537 | 0.9232 |
41 | 0.149 | 0.298 | 0.851 |
42 | 0.2649 | 0.5298 | 0.7351 |
43 | 0.3352 | 0.6703 | 0.6648 |
44 | 0.2985 | 0.5971 | 0.7015 |
45 | 0.3933 | 0.7866 | 0.6067 |
46 | 0.3664 | 0.7329 | 0.6336 |
47 | 0.3189 | 0.6378 | 0.6811 |
48 | 0.2734 | 0.5468 | 0.7266 |
49 | 0.2903 | 0.5806 | 0.7097 |
50 | 0.255 | 0.51 | 0.745 |
51 | 0.2501 | 0.5001 | 0.7499 |
52 | 0.2541 | 0.5081 | 0.7459 |
53 | 0.2869 | 0.5738 | 0.7131 |
54 | 0.3092 | 0.6184 | 0.6908 |
55 | 0.2602 | 0.5204 | 0.7398 |
56 | 0.2258 | 0.4516 | 0.7742 |
57 | 0.1875 | 0.375 | 0.8125 |
58 | 0.1992 | 0.3983 | 0.8008 |
59 | 0.2517 | 0.5034 | 0.7483 |
60 | 0.2085 | 0.417 | 0.7915 |
61 | 0.2186 | 0.4372 | 0.7814 |
62 | 0.2405 | 0.4809 | 0.7595 |
63 | 0.2094 | 0.4187 | 0.7906 |
64 | 0.1957 | 0.3914 | 0.8043 |
65 | 0.1921 | 0.3842 | 0.8079 |
66 | 0.4334 | 0.8667 | 0.5666 |
67 | 0.3949 | 0.7898 | 0.6051 |
68 | 0.3523 | 0.7047 | 0.6477 |
69 | 0.3178 | 0.6356 | 0.6822 |
70 | 0.2846 | 0.5691 | 0.7154 |
71 | 0.2483 | 0.4967 | 0.7517 |
72 | 0.2756 | 0.5512 | 0.7244 |
73 | 0.2822 | 0.5643 | 0.7178 |
74 | 0.3241 | 0.6483 | 0.6759 |
75 | 0.3133 | 0.6265 | 0.6867 |
76 | 0.5317 | 0.9366 | 0.4683 |
77 | 0.4837 | 0.9674 | 0.5163 |
78 | 0.4373 | 0.8747 | 0.5627 |
79 | 0.4261 | 0.8522 | 0.5739 |
80 | 0.3819 | 0.7638 | 0.6181 |
81 | 0.3904 | 0.7808 | 0.6096 |
82 | 0.422 | 0.8439 | 0.578 |
83 | 0.4295 | 0.8591 | 0.5705 |
84 | 0.4236 | 0.8471 | 0.5764 |
85 | 0.3773 | 0.7547 | 0.6227 |
86 | 0.7774 | 0.4451 | 0.2226 |
87 | 0.8059 | 0.3882 | 0.1941 |
88 | 0.861 | 0.278 | 0.139 |
89 | 0.8293 | 0.3414 | 0.1707 |
90 | 0.7937 | 0.4127 | 0.2063 |
91 | 0.7665 | 0.4669 | 0.2335 |
92 | 0.7357 | 0.5285 | 0.2643 |
93 | 0.708 | 0.584 | 0.292 |
94 | 0.7137 | 0.5725 | 0.2863 |
95 | 0.7394 | 0.5212 | 0.2606 |
96 | 0.7028 | 0.5943 | 0.2972 |
97 | 0.6613 | 0.6773 | 0.3387 |
98 | 0.6694 | 0.6613 | 0.3306 |
99 | 0.6408 | 0.7184 | 0.3592 |
100 | 0.5908 | 0.8184 | 0.4092 |
101 | 0.6209 | 0.7583 | 0.3791 |
102 | 0.5701 | 0.8597 | 0.4299 |
103 | 0.5278 | 0.9444 | 0.4722 |
104 | 0.5 | 1 | 0.5 |
105 | 0.5108 | 0.9784 | 0.4892 |
106 | 0.4657 | 0.9313 | 0.5343 |
107 | 0.4067 | 0.8134 | 0.5933 |
108 | 0.7315 | 0.5371 | 0.2685 |
109 | 0.6844 | 0.6313 | 0.3156 |
110 | 0.6846 | 0.6308 | 0.3154 |
111 | 0.7643 | 0.4713 | 0.2357 |
112 | 0.7188 | 0.5624 | 0.2812 |
113 | 0.7868 | 0.4264 | 0.2132 |
114 | 0.7545 | 0.491 | 0.2455 |
115 | 0.8745 | 0.2509 | 0.1255 |
116 | 0.8554 | 0.2891 | 0.1446 |
117 | 0.8098 | 0.3805 | 0.1902 |
118 | 0.7633 | 0.4733 | 0.2367 |
119 | 0.7577 | 0.4847 | 0.2423 |
120 | 0.7503 | 0.4993 | 0.2497 |
121 | 0.8555 | 0.2891 | 0.1445 |
122 | 0.7948 | 0.4104 | 0.2052 |
123 | 0.8479 | 0.3041 | 0.1521 |
124 | 0.8026 | 0.3948 | 0.1974 |
125 | 0.7427 | 0.5146 | 0.2573 |
126 | 0.6406 | 0.7189 | 0.3594 |
127 | 0.5216 | 0.9568 | 0.4784 |
128 | 0.5647 | 0.8707 | 0.4353 |
129 | 0.8975 | 0.2049 | 0.1025 |
130 | 0.8724 | 0.2553 | 0.1276 |
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 | 3 | 0.0280374 | OK |
Ramsey RESET F-Test for powers (2 and 3) of fitted values |
> reset_test_fitted RESET test data: mylm RESET = 6.4267, df1 = 2, df2 = 131, p-value = 0.002175 |
Ramsey RESET F-Test for powers (2 and 3) of regressors |
> reset_test_regressors RESET test data: mylm RESET = 1.1542, df1 = 40, df2 = 93, p-value = 0.2827 |
Ramsey RESET F-Test for powers (2 and 3) of principal components |
> reset_test_principal_components RESET test data: mylm RESET = 2.4541, df1 = 2, df2 = 131, p-value = 0.08988 |
Variance Inflation Factors (Multicollinearity) |
> vif Relative_Advantage Perceived_Usefulness Perceived_Ease_of_Use 1.950154 2.111059 2.818270 Information_Quality System_Quality groupB 3.524588 2.286771 1.398254 genderB `Intention_to_Use(t-1)` `Intention_to_Use(t-1s)` 1.249427 1.187090 1.192436 `Intention_to_Use(t-2s)` `Intention_to_Use(t-3s)` `Intention_to_Use(t-4s)` 1.340900 1.267167 1.173786 `Intention_to_Use(t-5s)` `Intention_to_Use(t-6s)` `Intention_to_Use(t-7s)` 1.187366 1.195849 1.200354 `Intention_to_Use(t-8s)` `Intention_to_Use(t-9s)` `Intention_to_Use(t-10s)` 1.210702 1.230331 1.170653 `Intention_to_Use(t-11s)` `Intention_to_Use(t-12s)` 1.175372 1.322717 |