Multiple Linear Regression - Estimated Regression Equation

Upset[t] = + 1.74601216389936 + 0.345463384070261punished[t] -0.154588829233689highstandards[t] + 0.488395323128333outstandingperformance[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)	1.74601216389936	0.614826	2.8398	0.0067	0.00335
punished	0.345463384070261	0.190041	1.8178	0.075605	0.037802
highstandards	-0.154588829233689	0.149388	-1.0348	0.306165	0.153083
outstandingperformance	0.488395323128333	0.18699	2.6119	0.012121	0.00606

Multiple Linear Regression - Regression Statistics
Multiple R	0.4156498702401
R-squared	0.172764814630612
Adjusted R-squared	0.118814693845652
F-TEST (value)	3.20230635477603
F-TEST (DF numerator)	3
F-TEST (DF denominator)	46
p-value	0.0318236506400493
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.941392931119065
Sum Squared Residuals	40.7661499350034

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	1	2.61615659670084	-1.61615659670084
2	2	2.61615659670084	-0.616156596700839
3	2	2.79537426136179	-0.795374261361794
4	2	2.61615659670084	-0.616156596700839
5	2	2.94996309059548	-0.949963090595484
6	2	1.9615155541632	0.0384844458367991
7	2	3.09289502965356	-1.09289502965356
8	3	2.80703115153741	0.192968848462588
9	4	2.46156776746715	1.53843223253285
10	2	2.27069321263058	-0.270693212630578
11	3	3.48630102950232	-0.486301029502317
12	4	3.77216490761846	0.227835092381539
13	4	3.29542647466574	0.704573525334255
14	2	2.46156776746715	-0.461567767467151
15	1	1.9615155541632	-0.961515554163201
16	1	2.93830620041987	-1.93830620041987
17	3	2.94996309059548	0.0500369094045162
18	2	2.94996309059548	-0.949963090595484
19	3	3.43835841372382	-0.438358413723817
20	4	3.28376958449013	0.716230415509872
21	4	2.27069321263058	1.72930678736942
22	4	2.64078543212811	1.35921456787189
23	4	3.48630102950232	0.513698970497683
24	4	3.10455191982917	0.895448080170827
25	2	2.94996309059548	-0.949963090595484
26	3	3.28376958449013	-0.283769584490128
27	2	2.79537426136180	-0.795374261361795
28	4	2.94996309059548	1.05003690940452
29	3	3.14083764543206	-0.140837645432056
30	2	2.79537426136180	-0.795374261361795
31	3	2.9136773649926	0.0863226350073999
32	4	3.97469635263065	0.0253036473693498
33	4	2.29532204805785	1.70467795194215
34	5	3.10455191982917	1.89544808017083
35	3	2.79537426136180	0.204625738638205
36	3	2.94996309059548	0.0500369094045162
37	4	3.10455191982917	0.895448080170827
38	2	2.30697893823346	-0.306978938233462
39	4	2.64078543212811	1.35921456787189
40	2	2.30697893823346	-0.306978938233462
41	3	2.79537426136180	0.204625738638205
42	2	2.79537426136180	-0.795374261361795
43	2	2.94996309059548	-0.949963090595484
44	2	2.79537426136180	-0.795374261361795
45	3	3.10455191982917	-0.104551919829173
46	3	3.24748385888724	-0.247483858887244
47	2	2.79537426136180	-0.795374261361795
48	4	2.75908853575891	1.24091146424109
49	4	2.79537426136180	1.20462573863821
50	4	3.4267015235482	0.5732984764518

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
7	0.149378395244868	0.298756790489736	0.850621604755132
8	0.151407130103597	0.302814260207195	0.848592869896403
9	0.574156756015742	0.851686487968516	0.425843243984258
10	0.461351568726021	0.922703137452041	0.538648431273979
11	0.344207001244693	0.688414002489386	0.655792998755307
12	0.422189806429408	0.844379612858817	0.577810193570592
13	0.439004557434518	0.878009114869036	0.560995442565482
14	0.35341500306786	0.70683000613572	0.64658499693214
15	0.353283073970068	0.706566147940136	0.646716926029932
16	0.520770788381002	0.958458423237995	0.479229211618998
17	0.447507240541248	0.895014481082497	0.552492759458752
18	0.421514715259406	0.843029430518812	0.578485284740594
19	0.349439921198886	0.698879842397771	0.650560078801114
20	0.373394480968654	0.746788961937307	0.626605519031346
21	0.667434914749568	0.665130170500864	0.332565085250432
22	0.742630451296415	0.51473909740717	0.257369548703585
23	0.697342770351217	0.605314459297567	0.302657229648783
24	0.709375871363842	0.581248257272317	0.290624128636158
25	0.707381109451712	0.585237781096575	0.292618890548288
26	0.639498700000928	0.721002599998144	0.360501299999072
27	0.622970185523623	0.754059628952753	0.377029814476377
28	0.641942656009776	0.716114687980448	0.358057343990224
29	0.556222076476102	0.887555847047795	0.443777923523898
30	0.542021306940084	0.915957386119833	0.457978693059916
31	0.466781267236727	0.933562534473454	0.533218732763273
32	0.418116759543104	0.836233519086207	0.581883240456896
33	0.531281150945247	0.937437698109507	0.468718849054753
34	0.775410076898416	0.449179846203167	0.224589923101584
35	0.695327474190985	0.60934505161803	0.304672525809015
36	0.598928095105313	0.802143809789374	0.401071904894687
37	0.677031264978315	0.64593747004337	0.322968735021685
38	0.599262788862624	0.801474422274751	0.400737211137376
39	0.695687150916397	0.608625698167206	0.304312849083603
40	0.605998194664823	0.788003610670354	0.394001805335177
41	0.493922056353549	0.987844112707097	0.506077943646451
42	0.40255792217865	0.8051158443573	0.59744207782135
43	0.309812585848867	0.619625171697734	0.690187414151133

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	0	0	OK