Multiple Linear Regression - Estimated Regression Equation |
Intention_to_Use[t] = -1.52273 + 0.151696System_Quality[t] + 0.0322698Information_Quality[t] + 0.226814Perceived_Ease_of_Use[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) | -1.523 | 0.9064 | -1.6800e+00 | 0.09473 | 0.04737 |
System_Quality | +0.1517 | 0.0325 | +4.6680e+00 | 6.029e-06 | 3.014e-06 |
Information_Quality | +0.03227 | 0.06818 | +4.7330e-01 | 0.6366 | 0.3183 |
Perceived_Ease_of_Use | +0.2268 | 0.05703 | +3.9770e+00 | 0.0001019 | 5.093e-05 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.6205 |
R-squared | 0.385 |
Adjusted R-squared | 0.3745 |
F-TEST (value) | 36.53 |
F-TEST (DF numerator) | 3 |
F-TEST (DF denominator) | 175 |
p-value | 0 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 1.553 |
Sum Squared Residuals | 421.9 |
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 | 6.884 | 3.116 |
2 | 8 | 7.444 | 0.5563 |
3 | 8 | 7.207 | 0.7928 |
4 | 9 | 8.246 | 0.7535 |
5 | 5 | 6.063 | -1.063 |
6 | 10 | 9.445 | 0.5549 |
7 | 8 | 8.472 | -0.4718 |
8 | 9 | 8.276 | 0.7242 |
9 | 8 | 5.651 | 2.349 |
10 | 7 | 8.441 | -1.441 |
11 | 10 | 8.3 | 1.7 |
12 | 10 | 7.328 | 2.672 |
13 | 9 | 7.316 | 1.684 |
14 | 4 | 6.019 | -2.019 |
15 | 4 | 7.662 | -3.662 |
16 | 8 | 7.986 | 0.01408 |
17 | 9 | 9.878 | -0.8785 |
18 | 10 | 6.464 | 3.536 |
19 | 8 | 7.393 | 0.6074 |
20 | 5 | 6.309 | -1.309 |
21 | 10 | 8.636 | 1.364 |
22 | 8 | 7.425 | 0.5751 |
23 | 7 | 7.12 | -0.1201 |
24 | 8 | 7.986 | 0.01408 |
25 | 8 | 9.955 | -1.955 |
26 | 9 | 7.173 | 1.827 |
27 | 8 | 7.693 | 0.3069 |
28 | 6 | 6.449 | -0.4487 |
29 | 8 | 6.784 | 1.216 |
30 | 8 | 6.32 | 1.68 |
31 | 5 | 7.987 | -2.987 |
32 | 9 | 8.395 | 0.6048 |
33 | 8 | 7.586 | 0.4143 |
34 | 8 | 6.892 | 1.108 |
35 | 8 | 7.379 | 0.6209 |
36 | 6 | 6.916 | -0.9159 |
37 | 6 | 6.232 | -0.2325 |
38 | 9 | 7.802 | 1.198 |
39 | 8 | 7.998 | 0.002045 |
40 | 9 | 9.564 | -0.5645 |
41 | 10 | 7.909 | 2.091 |
42 | 8 | 7.845 | 0.1552 |
43 | 8 | 5.595 | 2.405 |
44 | 7 | 7.146 | -0.1456 |
45 | 7 | 6.678 | 0.3215 |
46 | 10 | 7.858 | 2.142 |
47 | 8 | 6.145 | 1.855 |
48 | 7 | 6.007 | 0.9929 |
49 | 10 | 6.678 | 3.322 |
50 | 7 | 7.845 | -0.8448 |
51 | 7 | 5.434 | 1.566 |
52 | 9 | 8.907 | 0.09333 |
53 | 9 | 10.02 | -1.02 |
54 | 8 | 6.645 | 1.355 |
55 | 6 | 7.402 | -1.402 |
56 | 8 | 7.456 | 0.5443 |
57 | 9 | 7.011 | 1.989 |
58 | 2 | 4.978 | -2.978 |
59 | 6 | 6.568 | -0.5682 |
60 | 8 | 7.834 | 0.1658 |
61 | 8 | 9.079 | -1.079 |
62 | 7 | 6.783 | 0.2171 |
63 | 8 | 6.461 | 1.539 |
64 | 6 | 6.556 | -0.5561 |
65 | 10 | 6.633 | 3.367 |
66 | 10 | 7.531 | 2.469 |
67 | 10 | 7.088 | 2.912 |
68 | 8 | 6.721 | 1.279 |
69 | 8 | 7.273 | 0.7268 |
70 | 7 | 7.683 | -0.6825 |
71 | 10 | 9.869 | 0.1307 |
72 | 5 | 6.558 | -1.558 |
73 | 3 | 3.207 | -0.2068 |
74 | 2 | 4.125 | -2.125 |
75 | 3 | 4.957 | -1.957 |
76 | 4 | 6.404 | -2.404 |
77 | 2 | 5.002 | -3.002 |
78 | 6 | 5.131 | 0.8693 |
79 | 8 | 7.866 | 0.1335 |
80 | 8 | 7.759 | 0.2409 |
81 | 5 | 6.407 | -1.407 |
82 | 10 | 8.579 | 1.421 |
83 | 9 | 9.065 | -0.0651 |
84 | 8 | 9.217 | -1.217 |
85 | 9 | 8.397 | 0.6033 |
86 | 8 | 7.402 | 0.5982 |
87 | 5 | 5.897 | -0.8968 |
88 | 7 | 7.316 | -0.3161 |
89 | 9 | 8.883 | 0.1174 |
90 | 8 | 7.759 | 0.2409 |
91 | 4 | 7.089 | -3.089 |
92 | 7 | 5.305 | 1.695 |
93 | 8 | 8.645 | -0.6447 |
94 | 7 | 6.612 | 0.3875 |
95 | 7 | 6.331 | 0.6692 |
96 | 9 | 7.846 | 1.154 |
97 | 6 | 5.783 | 0.2168 |
98 | 7 | 7.478 | -0.4783 |
99 | 4 | 6.311 | -2.311 |
100 | 6 | 6.646 | -0.6462 |
101 | 10 | 7.879 | 2.121 |
102 | 9 | 7.273 | 1.727 |
103 | 10 | 9.445 | 0.5549 |
104 | 8 | 7.684 | 0.316 |
105 | 4 | 6.936 | -2.936 |
106 | 8 | 9.079 | -1.079 |
107 | 5 | 7.577 | -2.577 |
108 | 8 | 7.996 | 0.003505 |
109 | 9 | 8.257 | 0.743 |
110 | 8 | 7.282 | 0.7177 |
111 | 4 | 8.777 | -4.777 |
112 | 8 | 6.967 | 1.033 |
113 | 10 | 8.722 | 1.278 |
114 | 6 | 5.379 | 0.6213 |
115 | 7 | 6.157 | 0.8426 |
116 | 10 | 7.846 | 2.154 |
117 | 9 | 8.559 | 0.441 |
118 | 8 | 8.43 | -0.4304 |
119 | 3 | 6.21 | -3.21 |
120 | 8 | 6.72 | 1.28 |
121 | 7 | 7.347 | -0.3469 |
122 | 7 | 6.256 | 0.7444 |
123 | 8 | 5.801 | 2.199 |
124 | 8 | 7.877 | 0.1229 |
125 | 7 | 7.793 | -0.7928 |
126 | 7 | 6.818 | 0.1819 |
127 | 9 | 10.02 | -1.02 |
128 | 9 | 8.915 | 0.08514 |
129 | 9 | 7.357 | 1.643 |
130 | 4 | 7.39 | -3.39 |
131 | 6 | 7.197 | -1.197 |
132 | 6 | 6.311 | -0.3105 |
133 | 6 | 5.293 | 0.707 |
134 | 8 | 7.391 | 0.6088 |
135 | 3 | 6.449 | -3.449 |
136 | 8 | 7.12 | 0.88 |
137 | 8 | 8.539 | -0.5387 |
138 | 6 | 5.445 | 0.5553 |
139 | 10 | 8.668 | 1.332 |
140 | 2 | 5.436 | -3.436 |
141 | 9 | 8.148 | 0.8518 |
142 | 6 | 7.098 | -1.098 |
143 | 6 | 8.927 | -2.927 |
144 | 5 | 4.978 | 0.02246 |
145 | 4 | 5.216 | -1.216 |
146 | 7 | 6.116 | 0.884 |
147 | 5 | 6.893 | -1.893 |
148 | 8 | 7.727 | 0.2732 |
149 | 6 | 7.955 | -1.955 |
150 | 9 | 6.709 | 2.291 |
151 | 6 | 6.57 | -0.5696 |
152 | 4 | 5.445 | -1.445 |
153 | 7 | 7.65 | -0.6503 |
154 | 2 | 4.441 | -2.441 |
155 | 8 | 8.225 | -0.2248 |
156 | 9 | 7.77 | 1.23 |
157 | 6 | 6.343 | -0.3428 |
158 | 5 | 6.242 | -1.242 |
159 | 7 | 7.088 | -0.08778 |
160 | 8 | 6.999 | 1.001 |
161 | 4 | 6.418 | -2.418 |
162 | 9 | 7.466 | 1.534 |
163 | 9 | 9.391 | -0.3911 |
164 | 9 | 7.577 | 1.423 |
165 | 7 | 6.464 | 0.5363 |
166 | 5 | 6.677 | -1.677 |
167 | 7 | 8.018 | -1.018 |
168 | 9 | 10.08 | -1.084 |
169 | 8 | 7.101 | 0.8987 |
170 | 6 | 5.639 | 0.3608 |
171 | 9 | 8.32 | 0.6799 |
172 | 8 | 7.553 | 0.4466 |
173 | 7 | 8.269 | -1.269 |
174 | 7 | 7.131 | -0.1306 |
175 | 7 | 7.773 | -0.7726 |
176 | 8 | 7.089 | 0.9108 |
177 | 10 | 8.386 | 1.614 |
178 | 6 | 8.364 | -2.364 |
179 | 6 | 7.454 | -1.454 |
Goldfeld-Quandt test for Heteroskedasticity | |||
p-values | Alternative Hypothesis | ||
breakpoint index | greater | 2-sided | less |
7 | 0.7195 | 0.561 | 0.2805 |
8 | 0.5766 | 0.8468 | 0.4234 |
9 | 0.5462 | 0.9077 | 0.4538 |
10 | 0.5939 | 0.8122 | 0.4061 |
11 | 0.5434 | 0.9132 | 0.4566 |
12 | 0.54 | 0.92 | 0.46 |
13 | 0.4566 | 0.9133 | 0.5434 |
14 | 0.7585 | 0.483 | 0.2415 |
15 | 0.9561 | 0.08785 | 0.04392 |
16 | 0.9346 | 0.1307 | 0.06535 |
17 | 0.9093 | 0.1814 | 0.09071 |
18 | 0.9511 | 0.09786 | 0.04893 |
19 | 0.9303 | 0.1393 | 0.06965 |
20 | 0.9225 | 0.1549 | 0.07747 |
21 | 0.9066 | 0.1869 | 0.09344 |
22 | 0.8771 | 0.2459 | 0.1229 |
23 | 0.8398 | 0.3204 | 0.1602 |
24 | 0.7972 | 0.4056 | 0.2028 |
25 | 0.8118 | 0.3765 | 0.1882 |
26 | 0.8319 | 0.3362 | 0.1681 |
27 | 0.7902 | 0.4195 | 0.2098 |
28 | 0.7542 | 0.4915 | 0.2458 |
29 | 0.7204 | 0.5592 | 0.2796 |
30 | 0.7057 | 0.5887 | 0.2943 |
31 | 0.838 | 0.324 | 0.162 |
32 | 0.8054 | 0.3891 | 0.1946 |
33 | 0.7644 | 0.4711 | 0.2356 |
34 | 0.7265 | 0.547 | 0.2735 |
35 | 0.68 | 0.6399 | 0.32 |
36 | 0.6653 | 0.6695 | 0.3347 |
37 | 0.6301 | 0.7398 | 0.3699 |
38 | 0.6003 | 0.7994 | 0.3997 |
39 | 0.5475 | 0.905 | 0.4525 |
40 | 0.4962 | 0.9925 | 0.5038 |
41 | 0.5213 | 0.9573 | 0.4787 |
42 | 0.469 | 0.938 | 0.531 |
43 | 0.4787 | 0.9575 | 0.5213 |
44 | 0.4295 | 0.859 | 0.5705 |
45 | 0.3823 | 0.7647 | 0.6177 |
46 | 0.4278 | 0.8556 | 0.5722 |
47 | 0.4095 | 0.819 | 0.5905 |
48 | 0.3689 | 0.7378 | 0.6311 |
49 | 0.4886 | 0.9772 | 0.5114 |
50 | 0.4629 | 0.9257 | 0.5371 |
51 | 0.4356 | 0.8713 | 0.5644 |
52 | 0.3902 | 0.7804 | 0.6098 |
53 | 0.3529 | 0.7058 | 0.6471 |
54 | 0.3263 | 0.6527 | 0.6737 |
55 | 0.3369 | 0.6737 | 0.6631 |
56 | 0.2973 | 0.5945 | 0.7027 |
57 | 0.3027 | 0.6054 | 0.6973 |
58 | 0.5662 | 0.8676 | 0.4338 |
59 | 0.5376 | 0.9248 | 0.4624 |
60 | 0.4922 | 0.9844 | 0.5078 |
61 | 0.4662 | 0.9324 | 0.5338 |
62 | 0.4219 | 0.8438 | 0.5781 |
63 | 0.4087 | 0.8173 | 0.5913 |
64 | 0.3791 | 0.7583 | 0.6209 |
65 | 0.5217 | 0.9566 | 0.4783 |
66 | 0.5805 | 0.839 | 0.4195 |
67 | 0.6735 | 0.6531 | 0.3265 |
68 | 0.6541 | 0.6918 | 0.3459 |
69 | 0.6202 | 0.7596 | 0.3798 |
70 | 0.5929 | 0.8143 | 0.4071 |
71 | 0.5511 | 0.8979 | 0.4489 |
72 | 0.5794 | 0.8412 | 0.4206 |
73 | 0.573 | 0.854 | 0.427 |
74 | 0.6555 | 0.6889 | 0.3445 |
75 | 0.6942 | 0.6116 | 0.3058 |
76 | 0.7515 | 0.4971 | 0.2485 |
77 | 0.8409 | 0.3183 | 0.1591 |
78 | 0.8222 | 0.3556 | 0.1778 |
79 | 0.7939 | 0.4122 | 0.2061 |
80 | 0.7636 | 0.4729 | 0.2364 |
81 | 0.7626 | 0.4748 | 0.2374 |
82 | 0.7567 | 0.4866 | 0.2433 |
83 | 0.7223 | 0.5555 | 0.2777 |
84 | 0.7084 | 0.5831 | 0.2916 |
85 | 0.6767 | 0.6466 | 0.3233 |
86 | 0.6434 | 0.7133 | 0.3566 |
87 | 0.6145 | 0.7709 | 0.3855 |
88 | 0.5764 | 0.8473 | 0.4236 |
89 | 0.5347 | 0.9306 | 0.4653 |
90 | 0.4944 | 0.9889 | 0.5056 |
91 | 0.625 | 0.75 | 0.375 |
92 | 0.6341 | 0.7317 | 0.3659 |
93 | 0.5987 | 0.8026 | 0.4013 |
94 | 0.56 | 0.8799 | 0.44 |
95 | 0.5273 | 0.9454 | 0.4727 |
96 | 0.5097 | 0.9805 | 0.4903 |
97 | 0.4737 | 0.9474 | 0.5263 |
98 | 0.4347 | 0.8694 | 0.5653 |
99 | 0.4835 | 0.9671 | 0.5165 |
100 | 0.4478 | 0.8955 | 0.5522 |
101 | 0.4907 | 0.9813 | 0.5093 |
102 | 0.5104 | 0.9792 | 0.4896 |
103 | 0.4742 | 0.9485 | 0.5258 |
104 | 0.4379 | 0.8758 | 0.5621 |
105 | 0.5456 | 0.9088 | 0.4544 |
106 | 0.521 | 0.9581 | 0.479 |
107 | 0.5867 | 0.8266 | 0.4133 |
108 | 0.5432 | 0.9136 | 0.4568 |
109 | 0.5129 | 0.9743 | 0.4871 |
110 | 0.4799 | 0.9598 | 0.5201 |
111 | 0.8044 | 0.3912 | 0.1956 |
112 | 0.791 | 0.4181 | 0.209 |
113 | 0.7869 | 0.4263 | 0.2131 |
114 | 0.7607 | 0.4787 | 0.2393 |
115 | 0.741 | 0.518 | 0.259 |
116 | 0.7843 | 0.4313 | 0.2157 |
117 | 0.7547 | 0.4906 | 0.2453 |
118 | 0.7189 | 0.5621 | 0.2811 |
119 | 0.8239 | 0.3522 | 0.1761 |
120 | 0.8229 | 0.3542 | 0.1771 |
121 | 0.7915 | 0.417 | 0.2085 |
122 | 0.7697 | 0.4605 | 0.2303 |
123 | 0.8249 | 0.3502 | 0.1751 |
124 | 0.7942 | 0.4116 | 0.2058 |
125 | 0.7642 | 0.4716 | 0.2358 |
126 | 0.7305 | 0.5389 | 0.2695 |
127 | 0.706 | 0.588 | 0.294 |
128 | 0.6636 | 0.6728 | 0.3364 |
129 | 0.6895 | 0.6209 | 0.3105 |
130 | 0.8169 | 0.3662 | 0.1831 |
131 | 0.7962 | 0.4076 | 0.2038 |
132 | 0.7598 | 0.4804 | 0.2402 |
133 | 0.7456 | 0.5087 | 0.2544 |
134 | 0.7177 | 0.5647 | 0.2823 |
135 | 0.8469 | 0.3062 | 0.1531 |
136 | 0.8327 | 0.3345 | 0.1673 |
137 | 0.8004 | 0.3991 | 0.1996 |
138 | 0.7818 | 0.4364 | 0.2182 |
139 | 0.7811 | 0.4377 | 0.2189 |
140 | 0.8834 | 0.2331 | 0.1166 |
141 | 0.8754 | 0.2493 | 0.1246 |
142 | 0.8506 | 0.2987 | 0.1494 |
143 | 0.9197 | 0.1606 | 0.08029 |
144 | 0.8983 | 0.2034 | 0.1017 |
145 | 0.8773 | 0.2454 | 0.1227 |
146 | 0.8688 | 0.2624 | 0.1312 |
147 | 0.8798 | 0.2405 | 0.1202 |
148 | 0.8491 | 0.3018 | 0.1509 |
149 | 0.8706 | 0.2588 | 0.1294 |
150 | 0.9304 | 0.1392 | 0.0696 |
151 | 0.9061 | 0.1878 | 0.09389 |
152 | 0.8872 | 0.2256 | 0.1128 |
153 | 0.8551 | 0.2899 | 0.1449 |
154 | 0.8981 | 0.2038 | 0.1019 |
155 | 0.8627 | 0.2745 | 0.1373 |
156 | 0.8644 | 0.2713 | 0.1356 |
157 | 0.8218 | 0.3564 | 0.1782 |
158 | 0.8112 | 0.3776 | 0.1888 |
159 | 0.7541 | 0.4918 | 0.2459 |
160 | 0.7298 | 0.5403 | 0.2702 |
161 | 0.8397 | 0.3206 | 0.1603 |
162 | 0.8694 | 0.2613 | 0.1306 |
163 | 0.8536 | 0.2927 | 0.1464 |
164 | 0.8356 | 0.3287 | 0.1644 |
165 | 0.7678 | 0.4644 | 0.2322 |
166 | 0.8112 | 0.3775 | 0.1888 |
167 | 0.778 | 0.4439 | 0.222 |
168 | 0.6855 | 0.6289 | 0.3145 |
169 | 0.6057 | 0.7886 | 0.3943 |
170 | 0.4746 | 0.9492 | 0.5254 |
171 | 0.4236 | 0.8471 | 0.5764 |
172 | 0.4825 | 0.9649 | 0.5175 |
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 | 2 | 0.0120482 | OK |
Ramsey RESET F-Test for powers (2 and 3) of fitted values |
> reset_test_fitted RESET test data: mylm RESET = 4.6851, df1 = 2, df2 = 173, p-value = 0.01043 |
Ramsey RESET F-Test for powers (2 and 3) of regressors |
> reset_test_regressors RESET test data: mylm RESET = 2.3794, df1 = 6, df2 = 169, p-value = 0.03117 |
Ramsey RESET F-Test for powers (2 and 3) of principal components |
> reset_test_principal_components RESET test data: mylm RESET = 4.6541, df1 = 2, df2 = 173, p-value = 0.01075 |
Variance Inflation Factors (Multicollinearity) |
> vif System_Quality Information_Quality Perceived_Ease_of_Use 1.647271 2.586342 1.972540 |