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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Moduleesteq.wasp
Title produced by softwareEstimate Equation
Date of computationSat, 15 Mar 2008 22:48:24 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Mar/16/t12056451663ps8e55lq3fvn1e.htm/, Retrieved Sun, 19 May 2024 00:42:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=10075, Retrieved Sun, 19 May 2024 00:42:44 +0000
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User-defined keywords
Estimated Impact392

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12	30	900	52000	1
14	23	529	16100	0
14	31	961	50000	1
12	33	1089	41700	0
14	1	1	5800	0
18	24	576	30000	1
18	20	400	35000	0
12	28	784	18400	0
14	30	900	12500	0
14	40	1600	324000	1
9	7	49	26600	1
12	46	2116	21800	0
14	23	529	13000	0
11	3	9	4000	1
14	13	169	2400	0
12	16	256	40000	1
12	16	256	11500	0
11	17	289	120000	1
14	21	441	4800	0
12	26	676	2100	0
10	6	36	25000	1
14	22	484	56000	1
14	13	169	12000	0
11	1	1	800	1
14	26	676	20000	0
14	6	36	23000	1
14	23	529	1800	0
18	38	1444	60000	1
12	27	729	22100	0
16	25	625	16000	1
14	31	961	67000	1
14	-2	4	5000	1
14	29	841	57000	1
11	1	1	2000	1
14	5	25	35000	0
18	32	1024	324000	1
20	22	484	125000	0
	34	1156	18900	1
12	33	1089	16000	0
12	33	1089	62000	1
18	29	841	45000	1
16	22	484	27500	0
14	19	361	41000	1
14	13	169	3000	0
12	7	49	16000	0
14	11	121	15000	1
9	36	1296	25000	0
16	15	225	36000	1
14	64	4096	28200	1
14	17	289	36000	1
16	46	2116	130000	1
14	24	576	36000	1
12	10	100	12000	1
16	24	576	22000	0
11	0	0	5000	1
18	24	576	30200	0
12	13	169	14400	1
14	12	144	24800	0
12	40	1600	57000	0
12	40	1600	22000	1
9	35	1225	7000	0
16	23	529	23500	1
12	2	4	6600	0
12	1	1	20200	1
14	30	900	36500	1
14	26	676	21600	0
16	31	961	100000	1
12	30	900	9700	1
10	38	1444	10000	1
14	10	100	39100	1
16	35	1225	20400	0
12	1	1	4900	1
9	37	1369	100000	1
14	19	361	35000	1
14	20	400	10000	0
14	35	1225	37000	0
14	14	196	8000	0
14	23	529	10000	1
14	25	625	6000	0
12	13	169	30000	1
12	6	36	10200	1
12	1	1	6000	0
12	22	484	8000	1
16	12	144	26200	0
12	15	225	30000	0
20	54	2916	8000	1
16	24	576	34000	0
16	31	961	27500	1
10	4	16	500	0
12	6	36	35000	1
12	1	1	2400	0
11	1	1	6100	1
12	3	9	9000	1
14	37	1369	74000	1
20	22	484	31000	0
14	7	49	6600	1
11	21	441	16800	1
12	26	676	28700	1
12	17	289	12000	1
14	16	256	10600	0
16	5	25	4800	0
14	2	4	12000	1
14	3	9	10000	0
9	45	2025	6000	0
9	28	784	84000	1
14	6	36	29900	1
12	53	2809	324000	1
12	16	256	12000	0
10	29	841	2900	1
20	23	529	100000	0
14	9	81	35000	1
20	32	1024	88000	1
20	30	900	64000	0
12	23	529	38000	1
14	37	1369	58000	1
14	21	441	12000	1
16	1	1	21000	1
14	20	400	50000	1
12	25	625	11000	0
14	26	676	9100	0
16	6	36	27900	1
14	24	576	30000	1
14	21	441	7100	0
14	28	784	45000	1
14	1	1	1200	1
14	32	1024	20700	0
12	44	1936	40400	1
12	12	144	118000	1
14	39	1521	57000	1
16	46	2116	25500	1
16	20	400	80000	1
14	22	484	40000	0
14	4	16	8500	1
12	20	400	26000	0
11	22	484	26000	1
16	27	729	10900	0
14	25	625	46300	0
18	27	729	28200	0
14	5	25	21000	1
12	38	1444	38000	1
11	3	9	10000	0

Tables (Output of Computation)





Multiple Linear Regression - Estimated Regression Equation
ln(incwage[t]) = +0.10229152838667 school[t] +0.086791778577986 workexp[t] -0.001083642311728 work2[t] +0.75362724182658 gender[t] +6.9074313103488 + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
ln(incwage[t]) = +0.10229152838667 school[t] +0.086791778577986 workexp[t] -0.001083642311728 work2[t] +0.75362724182658 gender[t] +6.9074313103488 + e[t] \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=10075&T=0

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW]
ln(incwage[t]) = +0.10229152838667 school[t] +0.086791778577986 workexp[t] -0.001083642311728 work2[t] +0.75362724182658 gender[t] +6.9074313103488 + e[t][/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=10075&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=10075&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Estimated Regression Equation
ln(incwage[t]) = +0.10229152838667 school[t] +0.086791778577986 workexp[t] -0.001083642311728 work2[t] +0.75362724182658 gender[t] +6.9074313103488 + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.E.T-STATH0: parameter = 02-tail p-value1-tail p-value
school[t]0.1022920.0285223.5863940.0004660.000233
workexp[t]0.0867920.0163465.30958600
work2[t]-0.0010840.000331-3.2716980.0013550.000677
gender[t]0.7536270.1559444.8326744.0E-62.0E-6
Constant6.9074310.42833716.12617200
VariableElasticityS.E.*T-STATH0: |elast| = 12-tail p-value1-tail p-value
%school[t]0.1401110.039067-22.01049100
%workexp[t]0.186190.035067-23.20748100
%work2[t]-0.0686760.020991-44.36824100
%gender[t]0.0442940.009165-104.27280600
%Constant0.6980820.043289-6.97452500
VariableStand. Coeff.S.E.*T-STATH0: coeff = 02-tail p-value1-tail p-value
S-school[t]0.2433430.0678523.5863940.0004660.000233
S-workexp[t]1.0264990.1933295.30958600
S-work2[t]-0.6324080.193296-3.2716980.0013550.000677
S-gender[t]0.330960.0684844.8326744.0E-62.0E-6
S-Constant00010.5
*Notecomputed against deterministic endogenous series
VariablePartial Correlation
school[t]0.293945
workexp[t]0.414367
work2[t]-0.270117
gender[t]0.382829
Constant0.810316
Critical Values (alpha = 5%)
1-tail CV at 5%1.65
2-tail CV at 5%1.96

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Ordinary Least Squares \tabularnewline
VariableParameterS.E.T-STATH0: parameter = 02-tail p-value1-tail p-value \tabularnewline school[t]0.1022920.0285223.5863940.0004660.000233 \tabularnewline workexp[t]0.0867920.0163465.30958600 \tabularnewline work2[t]-0.0010840.000331-3.2716980.0013550.000677 \tabularnewline gender[t]0.7536270.1559444.8326744.0E-62.0E-6 \tabularnewline Constant6.9074310.42833716.12617200 \tabularnewline \tabularnewline VariableElasticityS.E.*T-STATH0: |elast| = 12-tail p-value1-tail p-value \tabularnewline %school[t]0.1401110.039067-22.01049100 \tabularnewline %workexp[t]0.186190.035067-23.20748100 \tabularnewline %work2[t]-0.0686760.020991-44.36824100 \tabularnewline %gender[t]0.0442940.009165-104.27280600 \tabularnewline %Constant0.6980820.043289-6.97452500 \tabularnewline VariableStand. Coeff.S.E.*T-STATH0: coeff = 02-tail p-value1-tail p-value \tabularnewline S-school[t]0.2433430.0678523.5863940.0004660.000233 \tabularnewline S-workexp[t]1.0264990.1933295.30958600 \tabularnewline S-work2[t]-0.6324080.193296-3.2716980.0013550.000677 \tabularnewline S-gender[t]0.330960.0684844.8326744.0E-62.0E-6 \tabularnewline S-Constant00010.5 \tabularnewline *Notecomputed against deterministic endogenous series \tabularnewline VariablePartial Correlation \tabularnewline school[t]0.293945 \tabularnewline workexp[t]0.414367 \tabularnewline work2[t]-0.270117 \tabularnewline gender[t]0.382829 \tabularnewline Constant0.810316 \tabularnewline Critical Values (alpha = 5%) \tabularnewline 1-tail CV at 5%1.65 \tabularnewline 2-tail CV at 5%1.96 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=10075&T=1

[TABLE]

[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]

[ROW]
Variable[/C]Parameter[/C]S.E.[/C]T-STATH0: parameter = 0[/C]2-tail p-value[/C]1-tail p-value[/C][/ROW] [ROW][C]school[t][/C]0.102292[/C]0.028522[/C]3.586394[/C]0.000466[/C]0.000233[/C][/ROW] [ROW][C]workexp[t][/C]0.086792[/C]0.016346[/C]5.309586[/C]0[/C]0[/C][/ROW] [ROW][C]work2[t][/C]-0.001084[/C]0.000331[/C]-3.271698[/C]0.001355[/C]0.000677[/C][/ROW] [ROW][C]gender[t][/C]0.753627[/C]0.155944[/C]4.832674[/C]4.0E-6[/C]2.0E-6[/C][/ROW] [ROW][C]Constant[/C]6.907431[/C]0.428337[/C]16.126172[/C]0[/C]0[/C][/ROW] [ROW][C][/C][/ROW] [ROW]Variable[/C]Elasticity[/C]S.E.*[/C]T-STATH0: |elast| = 1[/C]2-tail p-value[/C]1-tail p-value[/C][/ROW] [ROW][C]%school[t][/C]0.140111[/C]0.039067[/C]-22.010491[/C]0[/C]0[/C][/ROW] [ROW][C]%workexp[t][/C]0.18619[/C]0.035067[/C]-23.207481[/C]0[/C]0[/C][/ROW] [ROW][C]%work2[t][/C]-0.068676[/C]0.020991[/C]-44.368241[/C]0[/C]0[/C][/ROW] [ROW][C]%gender[t][/C]0.044294[/C]0.009165[/C]-104.272806[/C]0[/C]0[/C][/ROW] [ROW][C]%Constant[/C]0.698082[/C]0.043289[/C]-6.974525[/C]0[/C]0[/C][/ROW] [ROW]Variable[/C]Stand. Coeff.[/C]S.E.*[/C]T-STATH0: coeff = 0[/C]2-tail p-value[/C]1-tail p-value[/C][/ROW] [ROW][C]S-school[t][/C]0.243343[/C]0.067852[/C]3.586394[/C]0.000466[/C]0.000233[/C][/ROW] [ROW][C]S-workexp[t][/C]1.026499[/C]0.193329[/C]5.309586[/C]0[/C]0[/C][/ROW] [ROW][C]S-work2[t][/C]-0.632408[/C]0.193296[/C]-3.271698[/C]0.001355[/C]0.000677[/C][/ROW] [ROW][C]S-gender[t][/C]0.33096[/C]0.068484[/C]4.832674[/C]4.0E-6[/C]2.0E-6[/C][/ROW] [ROW][C]S-Constant[/C]0[/C]0[/C]0[/C]1[/C]0.5[/C][/ROW] [ROW][C]*Note[/C]computed against deterministic endogenous series[/C][/ROW] [ROW]Variable[/C]Partial Correlation[/C][/ROW] [ROW][C]school[t][/C]0.293945[/C][/ROW] [ROW][C]workexp[t][/C]0.414367[/C][/ROW] [ROW][C]work2[t][/C]-0.270117[/C][/ROW] [ROW][C]gender[t][/C]0.382829[/C][/ROW] [ROW][C]Constant[/C]0.810316[/C][/ROW] [ROW][C]Critical Values (alpha = 5%)[/C][/ROW] [ROW][C]1-tail CV at 5%[/C]1.65[/C][/ROW] [ROW][C]2-tail CV at 5%[/C]1.96[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=10075&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=10075&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.E.T-STATH0: parameter = 02-tail p-value1-tail p-value
school[t]0.1022920.0285223.5863940.0004660.000233
workexp[t]0.0867920.0163465.30958600
work2[t]-0.0010840.000331-3.2716980.0013550.000677
gender[t]0.7536270.1559444.8326744.0E-62.0E-6
Constant6.9074310.42833716.12617200
VariableElasticityS.E.*T-STATH0: |elast| = 12-tail p-value1-tail p-value
%school[t]0.1401110.039067-22.01049100
%workexp[t]0.186190.035067-23.20748100
%work2[t]-0.0686760.020991-44.36824100
%gender[t]0.0442940.009165-104.27280600
%Constant0.6980820.043289-6.97452500
VariableStand. Coeff.S.E.*T-STATH0: coeff = 02-tail p-value1-tail p-value
S-school[t]0.2433430.0678523.5863940.0004660.000233
S-workexp[t]1.0264990.1933295.30958600
S-work2[t]-0.6324080.193296-3.2716980.0013550.000677
S-gender[t]0.330960.0684844.8326744.0E-62.0E-6
S-Constant00010.5
*Notecomputed against deterministic endogenous series
VariablePartial Correlation
school[t]0.293945
workexp[t]0.414367
work2[t]-0.270117
gender[t]0.382829
Constant0.810316
Critical Values (alpha = 5%)
1-tail CV at 5%1.65
2-tail CV at 5%1.96






Multiple Linear Regression - Regression Statistics
Multiple R0.629172
R-squared0.395857
Adjusted R-squared0.378088
F-TEST22.278071
Observations141
Degrees of Freedom136
Multiple Linear Regression - Residual Statistics
Standard Error0.889005
Sum Squared Errors107.484912
Log Likelihood-180.93597
Durbin-Watson2.126934
Von Neumann Ratio2.142127
# e[t] > 076
# e[t] < 065
# Runs79
Stand. Normal Runs Statistic1.34856

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Regression Statistics \tabularnewline

Multiple R
0.629172 \tabularnewline R-squared0.395857 \tabularnewline Adjusted R-squared0.378088 \tabularnewline F-TEST22.278071 \tabularnewline Observations141 \tabularnewline Degrees of Freedom136 \tabularnewline Multiple Linear Regression - Residual Statistics \tabularnewline Standard Error0.889005 \tabularnewline Sum Squared Errors107.484912 \tabularnewline Log Likelihood-180.93597 \tabularnewline Durbin-Watson2.126934 \tabularnewline Von Neumann Ratio2.142127 \tabularnewline # e[t] > 076 \tabularnewline # e[t] < 065 \tabularnewline # Runs79 \tabularnewline Stand. Normal Runs Statistic1.34856 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=10075&T=2

[TABLE]

[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]

[ROW][C]Multiple R[/C]
0.629172[/C][/ROW] [ROW][C]R-squared[/C]0.395857[/C][/ROW] [ROW][C]Adjusted R-squared[/C]0.378088[/C][/ROW] [ROW][C]F-TEST[/C]22.278071[/C][/ROW] [ROW][C]Observations[/C]141[/C][/ROW] [ROW][C]Degrees of Freedom[/C]136[/C][/ROW] [ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW] [ROW][C]Standard Error[/C]0.889005[/C][/ROW] [ROW][C]Sum Squared Errors[/C]107.484912[/C][/ROW] [ROW][C]Log Likelihood[/C]-180.93597[/C][/ROW] [ROW][C]Durbin-Watson[/C]2.126934[/C][/ROW] [ROW][C]Von Neumann Ratio[/C]2.142127[/C][/ROW] [ROW][C]# e[t] > 0[/C]76[/C][/ROW] [ROW][C]# e[t] < 0[/C]65[/C][/ROW] [ROW][C]# Runs[/C]79[/C][/ROW] [ROW][C]Stand. Normal Runs Statistic[/C]1.34856[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=10075&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=10075&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Regression Statistics
Multiple R0.629172
R-squared0.395857
Adjusted R-squared0.378088
F-TEST22.278071
Observations141
Degrees of Freedom136
Multiple Linear Regression - Residual Statistics
Standard Error0.889005
Sum Squared Errors107.484912
Log Likelihood-180.93597
Durbin-Watson2.126934
Von Neumann Ratio2.142127
# e[t] > 076
# e[t] < 065
# Runs79
Stand. Normal Runs Statistic1.34856






Multiple Linear Regression - Ad Hoc Selection Test Statistics
Akaike (1969) Final Prediction Error0.818356
Akaike (1973) Log Information Criterion-0.200487
Akaike (1974) Information Criterion0.818332
Schwarz (1978) Log Criterion-0.095921
Schwarz (1978) Criterion0.908535
Craven-Wahba (1979) Generalized Cross Validation0.819386
Hannan-Quinn (1979) Criterion0.853854
Rice (1984) Criterion0.820496
Shibata (1981) Criterion0.816368

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Ad Hoc Selection Test Statistics \tabularnewline

Akaike (1969) Final Prediction Error
0.818356 \tabularnewline Akaike (1973) Log Information Criterion-0.200487 \tabularnewline Akaike (1974) Information Criterion0.818332 \tabularnewline Schwarz (1978) Log Criterion-0.095921 \tabularnewline Schwarz (1978) Criterion0.908535 \tabularnewline Craven-Wahba (1979) Generalized Cross Validation0.819386 \tabularnewline Hannan-Quinn (1979) Criterion0.853854 \tabularnewline Rice (1984) Criterion0.820496 \tabularnewline Shibata (1981) Criterion0.816368 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=10075&T=3

[TABLE]

[ROW][C]Multiple Linear Regression - Ad Hoc Selection Test Statistics[/C][/ROW]

[ROW][C]Akaike (1969) Final Prediction Error[/C]
0.818356[/C][/ROW] [ROW][C]Akaike (1973) Log Information Criterion[/C]-0.200487[/C][/ROW] [ROW][C]Akaike (1974) Information Criterion[/C]0.818332[/C][/ROW] [ROW][C]Schwarz (1978) Log Criterion[/C]-0.095921[/C][/ROW] [ROW][C]Schwarz (1978) Criterion[/C]0.908535[/C][/ROW] [ROW][C]Craven-Wahba (1979) Generalized Cross Validation[/C]0.819386[/C][/ROW] [ROW][C]Hannan-Quinn (1979) Criterion[/C]0.853854[/C][/ROW] [ROW][C]Rice (1984) Criterion[/C]0.820496[/C][/ROW] [ROW][C]Shibata (1981) Criterion[/C]0.816368[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=10075&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=10075&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Ad Hoc Selection Test Statistics
Akaike (1969) Final Prediction Error0.818356
Akaike (1973) Log Information Criterion-0.200487
Akaike (1974) Information Criterion0.818332
Schwarz (1978) Log Criterion-0.095921
Schwarz (1978) Criterion0.908535
Craven-Wahba (1979) Generalized Cross Validation0.819386
Hannan-Quinn (1979) Criterion0.853854
Rice (1984) Criterion0.820496
Shibata (1981) Criterion0.816368






Ramsey RESET test for Misspecification

Multiple Linear Regression - Analysis of Variance
ANOVADFSum of SquaresMean Square
Regression470.42813317.607033
Residual136107.4849120.79033
Total140177.9130451.27080746112
F-TEST22.278071
p-value0

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Analysis of Variance \tabularnewline

ANOVA & DF & Sum of Squares & Mean Square \tabularnewline

Regression
470.42813317.607033 \tabularnewline Residual136107.4849120.79033 \tabularnewline Total140177.9130451.27080746112 \tabularnewline F-TEST22.278071 \tabularnewline p-value0 \tabularnewline

Ramsey RESET test for Misspecification

\hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=10075&T=4

[TABLE]

[ROW][C]Multiple Linear Regression - Analysis of Variance[/C][/ROW]

[ROW][C]ANOVA[/C][C]DF[/C][C]Sum of Squares[/C][C]Mean Square[/C][/ROW]

[ROW][C]Regression[/C]
4[/C]70.428133[/C]17.607033[/C][/ROW] [ROW][C]Residual[/C]136[/C]107.484912[/C]0.79033[/C][/ROW] [ROW][C]Total[/C]140[/C]177.913045[/C]1.27080746112[/C][/ROW] [ROW][C]F-TEST[/C]22.278071[/C][/ROW] [ROW][C]p-value[/C]0[/C][/ROW]

Ramsey RESET test for Misspecification

[/TABLE] Source: https://freestatistics.org/blog/index.php?pk=10075&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=10075&T=4

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Ramsey RESET test for Misspecification

Multiple Linear Regression - Analysis of Variance
ANOVADFSum of SquaresMean Square
Regression470.42813317.607033
Residual136107.4849120.79033
Total140177.9130451.27080746112
F-TEST22.278071
p-value0






Multiple Linear Regression - Help Regression
VariableParameterS.E.T-STATH0: parameter = 02-tail p-value1-tail p-value
school[t]0.1084230.0517992.0931380.0382360.019118
workexp[t]0.0795360.0351962.259790.025460.01273
work2[t]-0.0009530.000507-1.8777420.0626060.031303
gender [t]0.7428320.34972.1241990.0355040.017752
@F[t]^2000.3507040.7263650.363183
@F[t]^3-00-0.3853910.7005630.350282
@F[t]^4000.3594210.719850.359925
Constant6.8118690.8813037.7293200

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Help Regression \tabularnewline
VariableParameterS.E.T-STATH0: parameter = 02-tail p-value1-tail p-value \tabularnewline school[t]0.1084230.0517992.0931380.0382360.019118 \tabularnewline workexp[t]0.0795360.0351962.259790.025460.01273 \tabularnewline work2[t]-0.0009530.000507-1.8777420.0626060.031303 \tabularnewline gender [t]0.7428320.34972.1241990.0355040.017752 \tabularnewline @F[t]^2000.3507040.7263650.363183 \tabularnewline @F[t]^3-00-0.3853910.7005630.350282 \tabularnewline @F[t]^4000.3594210.719850.359925 \tabularnewline Constant6.8118690.8813037.7293200 \tabularnewline \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=10075&T=5

[TABLE]

[ROW][C]Multiple Linear Regression - Help Regression[/C][/ROW]

[ROW]
Variable[/C]Parameter[/C]S.E.[/C]T-STATH0: parameter = 0[/C]2-tail p-value[/C]1-tail p-value[/C][/ROW] [ROW][C]school[t][/C]0.108423[/C]0.051799[/C]2.093138[/C]0.038236[/C]0.019118[/C][/ROW] [ROW][C]workexp[t][/C]0.079536[/C]0.035196[/C]2.25979[/C]0.02546[/C]0.01273[/C][/ROW] [ROW][C]work2[t][/C]-0.000953[/C]0.000507[/C]-1.877742[/C]0.062606[/C]0.031303[/C][/ROW] [ROW][C]gender [t][/C]0.742832[/C]0.3497[/C]2.124199[/C]0.035504[/C]0.017752[/C][/ROW] [ROW][C]@F[t]^2[/C]0[/C]0[/C]0.350704[/C]0.726365[/C]0.363183[/C][/ROW] [ROW][C]@F[t]^3[/C]-0[/C]0[/C]-0.385391[/C]0.700563[/C]0.350282[/C][/ROW] [ROW][C]@F[t]^4[/C]0[/C]0[/C]0.359421[/C]0.71985[/C]0.359925[/C][/ROW] [ROW][C]Constant[/C]6.811869[/C]0.881303[/C]7.72932[/C]0[/C]0[/C][/ROW] [ROW][C][/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=10075&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=10075&T=5

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Help Regression
VariableParameterS.E.T-STATH0: parameter = 02-tail p-value1-tail p-value
school[t]0.1084230.0517992.0931380.0382360.019118
workexp[t]0.0795360.0351962.259790.025460.01273
work2[t]-0.0009530.000507-1.8777420.0626060.031303
gender [t]0.7428320.34972.1241990.0355040.017752
@F[t]^2000.3507040.7263650.363183
@F[t]^3-00-0.3853910.7005630.350282
@F[t]^4000.3594210.719850.359925
Constant6.8118690.8813037.7293200






Multiple Linear Regression - Help Regression Statistics
Multiple R0.632458
R-squared0.400003
F-TEST12.66684
p-value0
Standard Error0.895886
Observations141
Degrees of Freedom133

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Help Regression Statistics \tabularnewline

Multiple R
0.632458 \tabularnewline R-squared0.400003 \tabularnewline F-TEST12.66684 \tabularnewline p-value0 \tabularnewline Standard Error0.895886 \tabularnewline Observations141 \tabularnewline Degrees of Freedom133 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=10075&T=6

[TABLE]

[ROW][C]Multiple Linear Regression - Help Regression Statistics[/C][/ROW]

[ROW][C]Multiple R[/C]
0.632458[/C][/ROW] [ROW][C]R-squared[/C]0.400003[/C][/ROW] [ROW][C]F-TEST[/C]12.66684[/C][/ROW] [ROW][C]p-value[/C]0[/C][/ROW] [ROW][C]Standard Error[/C]0.895886[/C][/ROW] [ROW][C]Observations[/C]141[/C][/ROW] [ROW][C]Degrees of Freedom[/C]133[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=10075&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=10075&T=6

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Help Regression Statistics
Multiple R0.632458
R-squared0.400003
F-TEST12.66684
p-value0
Standard Error0.895886
Observations141
Degrees of Freedom133






Ramsey RESET Test for Misspecification - Reduction F-test
SSR Ramsey Model106.747244
SSR Reduced Model107.484912
# Reduced Parameters3
Degrees of Freedom133
Reduction F-test0.3133
p-value0.815761

\begin{tabular}{lllllllll}
\hline

Ramsey RESET Test for Misspecification - Reduction F-test \tabularnewline

SSR Ramsey Model
106.747244 \tabularnewline SSR Reduced Model107.484912 \tabularnewline # Reduced Parameters3 \tabularnewline Degrees of Freedom133 \tabularnewline Reduction F-test0.3133 \tabularnewline p-value0.815761 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=10075&T=7

[TABLE]

[ROW][C]Ramsey RESET Test for Misspecification - Reduction F-test[/C][/ROW]

[ROW][C]SSR Ramsey Model[/C]
106.747244[/C][/ROW] [ROW][C]SSR Reduced Model[/C]107.484912[/C][/ROW] [ROW][C]# Reduced Parameters[/C]3[/C][/ROW] [ROW][C]Degrees of Freedom[/C]133[/C][/ROW] [ROW][C]Reduction F-test[/C]0.3133[/C][/ROW] [ROW][C]p-value[/C]0.815761[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=10075&T=7

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=10075&T=7

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Ramsey RESET Test for Misspecification - Reduction F-test
SSR Ramsey Model106.747244
SSR Reduced Model107.484912
# Reduced Parameters3
Degrees of Freedom133
Reduction F-test0.3133
p-value0.815761


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):