Multiple Linear Regression - Estimated Regression Equation
NEUROTICISM[t] = + 3.63021 -0.263251EXTRAVERSION[t] + 0.442822AGREEABLENESS[t] + 0.207943CONSCIENTIOUSNESS[t] -0.441248OPENNESS[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0		2-tail p-value1-tail p-value
(Intercept)+3.63 0.811+4.4760e+00 2.198e-05 1.099e-05
EXTRAVERSION-0.2632 0.1025-2.5680e+00 0.01186 0.005932
AGREEABLENESS+0.4428 0.1066+4.1540e+00 7.362e-05 3.681e-05
CONSCIENTIOUSNESS+0.2079 0.1511+1.3760e+00 0.1721 0.08603
OPENNESS-0.4412 0.1379-3.2000e+00 0.001892 0.000946


Multiple Linear Regression - Regression Statistics
Multiple R 0.5545
R-squared 0.3075
Adjusted R-squared 0.2771
F-TEST (value) 10.1
F-TEST (DF numerator)4
F-TEST (DF denominator)91
p-value 8.217e-07
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation 1.202
Sum Squared Residuals 131.5


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 4 3.625 0.3752
2 4 3.209 0.7911
3 4 3.179 0.8212
4 4 3.625 0.3752
5 4 4.949-0.9485
6 4 2.295 1.705
7 4 4.298-0.2978
8 4 3.209 0.7911
9 4 5.034-1.034
10 4 3.266 0.7344
11 4 3.734 0.2662
12 2 3.527-1.527
13 2 3.501-1.501
14 3 3.732-0.7323
15 3 3.732-0.7323
16 5 4.826 0.1742
17 5 4.826 0.1742
18 5 3.942 1.058
19 5 4.618 0.3821
20 5 3.943 1.057
21 5 4.151 0.8487
22 5 4.824 0.1757
23 5 3.708 1.292
24 5 4.771 0.2295
25 5 3.886 1.114
26 5 3.472 1.528
27 5 4.121 0.8787
28 5 4.328 0.6723
29 5 2.56 2.44
30 5 4.329 0.6707
31 5 4.12 0.8802
32 5 4.145 0.8549
33 5 4.121 0.8787
34 5 3.886 1.114
35 5 3.026 1.974
36 5 3.886 1.114
37 5 3.888 1.112
38 5 3.36 1.64
39 5 4.856 0.1442
40 5 4.413 0.587
41 5 3.527 1.473
42 5 4.411 0.5886
43 5 4.203 0.7965
44 5 4.203 0.7965
45 5 5.297-0.297
46 1 4.415-3.415
47 1 3.992-2.992
48 1 3.764-2.764
49 2 2.033-0.03307
50 4 3.358 0.6416
51 2 2.739-0.7391
52 4 3.707 0.2931
53 1 2.558-1.558
54 2 3.888-1.888
55 4 3.236 0.7643
56 2 2.293-0.2933
57 4 2.794 1.206
58 4 2.474 1.526
59 2 2.53-0.5296
60 4 3.15 0.8496
61 1 2.709-1.709
62 3 3.469-0.469
63 3 3.469-0.469
64 2 3.649-1.649
65 2 2.033-0.03307
66 3 2.531 0.4688
67 1 3.593-2.593
68 1 2.739-1.739
69 3 2.738 0.2624
70 1 2.919-1.919
71 2 2.711-0.7108
72 2 2.033-0.03307
73 2 3.182-1.182
74 1 2.033-1.033
75 5 3.362 1.638
76 2 2.972-0.9724
77 4 4.15-0.1497
78 2 2.296-0.2963
79 2 2.738-0.7376
80 2 3.264-1.264
81 2 3.445-1.445
82 2 2.476-0.4759
83 4 2.999 1.001
84 2 3.18-1.18
85 2 2.033-0.03307
86 4 2.972 1.028
87 3 3.801-0.8012
88 4 2.531 1.469
89 4 3.086 0.9139
90 1 3.001-2.001
91 4 3.857 0.1435
92 2 2.296-0.2963
93 2 3.002-1.002
94 3 2.739 0.2609
95 4 3.05 0.95
96 3 3.445-0.4452


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
8 9.399e-46 1.88e-45 1
9 0 0 1
10 0 0 1
11 9.889e-91 1.978e-90 1
12 0.01314 0.02628 0.9869
13 0.0434 0.0868 0.9566
14 0.02225 0.0445 0.9778
15 0.01089 0.02178 0.9891
16 0.02835 0.0567 0.9717
17 0.03348 0.06696 0.9665
18 0.04796 0.09593 0.952
19 0.05066 0.1013 0.9493
20 0.05256 0.1051 0.9474
21 0.03829 0.07658 0.9617
22 0.02751 0.05502 0.9725
23 0.0221 0.0442 0.9779
24 0.01341 0.02682 0.9866
25 0.009772 0.01954 0.9902
26 0.01471 0.02943 0.9853
27 0.01135 0.02269 0.9887
28 0.007385 0.01477 0.9926
29 0.01153 0.02305 0.9885
30 0.007494 0.01499 0.9925
31 0.006119 0.01224 0.9939
32 0.007923 0.01585 0.9921
33 0.00621 0.01242 0.9938
34 0.004758 0.009515 0.9952
35 0.007793 0.01559 0.9922
36 0.006217 0.01243 0.9938
37 0.0055 0.011 0.9945
38 0.005572 0.01114 0.9944
39 0.003885 0.00777 0.9961
40 0.003007 0.006014 0.997
41 0.003089 0.006178 0.9969
42 0.002389 0.004778 0.9976
43 0.002284 0.004568 0.9977
44 0.002416 0.004833 0.9976
45 0.002249 0.004498 0.9978
46 0.07774 0.1555 0.9223
47 0.3464 0.6929 0.6536
48 0.6014 0.7972 0.3986
49 0.6475 0.705 0.3525
50 0.6482 0.7036 0.3518
51 0.6685 0.6631 0.3315
52 0.6288 0.7424 0.3712
53 0.7324 0.5352 0.2676
54 0.7878 0.4244 0.2122
55 0.7655 0.469 0.2345
56 0.7361 0.5277 0.2639
57 0.7375 0.5249 0.2625
58 0.7859 0.4283 0.2141
59 0.7604 0.4793 0.2396
60 0.7798 0.4404 0.2202
61 0.8391 0.3218 0.1609
62 0.8011 0.3977 0.1989
63 0.7587 0.4826 0.2413
64 0.7984 0.4031 0.2016
65 0.7589 0.4822 0.2411
66 0.7074 0.5853 0.2926
67 0.8626 0.2748 0.1374
68 0.8952 0.2097 0.1048
69 0.8722 0.2556 0.1278
70 0.9132 0.1736 0.08682
71 0.9064 0.1873 0.09365
72 0.8723 0.2554 0.1277
73 0.8684 0.2633 0.1316
74 0.8519 0.2963 0.1481
75 0.9267 0.1466 0.07329
76 0.9249 0.1503 0.07514
77 0.9013 0.1974 0.0987
78 0.8587 0.2826 0.1413
79 0.8107 0.3787 0.1893
80 0.7903 0.4195 0.2097
81 0.7925 0.415 0.2075
82 0.717 0.566 0.283
83 0.9175 0.165 0.08251
84 0.8723 0.2555 0.1277
85 0.795 0.41 0.205
86 0.7257 0.5485 0.2743
87 0.6851 0.6297 0.3149
88 0.5312 0.9376 0.4688


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level12 0.1481NOK
5% type I error level300.37037NOK
10% type I error level360.444444NOK


Ramsey RESET F-Test for powers (2 and 3) of fitted values
> reset_test_fitted
	RESET test
data:  mylm
RESET = 0.19327, df1 = 2, df2 = 89, p-value = 0.8246
Ramsey RESET F-Test for powers (2 and 3) of regressors
> reset_test_regressors
	RESET test
data:  mylm
RESET = 1.3648, df1 = 8, df2 = 83, p-value = 0.2241
Ramsey RESET F-Test for powers (2 and 3) of principal components
> reset_test_principal_components
	RESET test
data:  mylm
RESET = 1.6751, df1 = 2, df2 = 89, p-value = 0.1931


Variance Inflation Factors (Multicollinearity)
> vif
     EXTRAVERSION     AGREEABLENESS CONSCIENTIOUSNESS          OPENNESS 
         1.095885          1.067808          1.200097          1.263476