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R Software Module

esteq.wasp

Title produced by software

Estimate Equation

Date of computation

Wed, 11 Jun 2014 16:26:02 +0200

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Jun/11/t1402497128pxtoz8iivapwu4k.htm/, Retrieved Wed, 15 May 2024 15:28:01 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=235230, Retrieved Wed, 15 May 2024 15:28:01 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Violencia, homicidio, pobreza, inequidad, gini

Estimated Impact

215

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Estimate Equation] [Correlacion linea...] [2014-06-11 14:26:02] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Dataseries X:

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Histogram

Boxplots

99.2	96.7	101.0
99.0	98.1	100.1
5.50	44.5	30.00
12.10	56.3	51.30
25.20	54.7	21.40
1.60	32.6	9.40
3.10	52.1	14.40
30.80	55.9	34.10
8.50	50.7	24.80
12.40	49.3	28.60
41.20	48.3	25.77
4.70	40.8	15.10
39.90	55.8	53.70
90.40	57.0	66.20
21.50	47.2	51.30
11.30	40.5	42.50
17.20	51.9	32.70
9.70	52.4	32.40
9.60	48.1	27.80
22.10	47.2	40.40
7.90	45.3	13.70
53.70	44.8	31.90

Multiple Linear Regression - Estimated Regression Equation
Homicidios[t] = +0.48333621373442 Gini[t] +0.79614967387558 Pobreza[t] -27.935853003301 + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline

Homicidios[t] = +0.48333621373442 Gini[t] +0.79614967387558 Pobreza[t] -27.935853003301 + e[t] \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=235230&T=0

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW]

Homicidios[t] = +0.48333621373442 Gini[t] +0.79614967387558 Pobreza[t] -27.935853003301 + e[t][/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=235230&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235230&T=0

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Estimated Regression Equation
Homicidios[t] = +0.48333621373442 Gini[t] +0.79614967387558 Pobreza[t] -27.935853003301 + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.E.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
Gini[t]	0.483336	0.467912	1.032965	0.31459	0.157295
Pobreza[t]	0.79615	0.294906	2.699669	0.014199	0.0071
Constant	-27.935853	16.448553	-1.698378	0.105754	0.052877

Variable	Elasticity	S.E.^*	T-STATH0: \|elast\| = 1	2-tail p-value	1-tail p-value
%Gini[t]	0.902649	0.873843	-0.111405	0.912463	0.456232
%Pobreza[t]	1.078182	0.399376	0.19576	0.846876	0.423438
%Constant	-0.980831	0.577511	-0.033192	0.973867	0.486934
Variable	Stand. Coeff.	S.E.^*	T-STATH0: coeff = 0	2-tail p-value	1-tail p-value
S-Gini[t]	0.244045	0.236257	1.032965	0.31459	0.157295
S-Pobreza[t]	0.637816	0.236257	2.699669	0.014199	0.0071
S-Constant	0	0	0	1	0.5
^*Note	computed against deterministic endogenous series
Variable	Partial Correlation
Gini[t]	0.230592
Pobreza[t]	0.526538
Constant	-0.36305
Critical Values (alpha = 5%)
1-tail CV at 5%	1.73
2-tail CV at 5%	2.09

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Ordinary Least Squares \tabularnewline

Variable

Parameter

S.E.

T-STATH0: parameter = 0

2-tail p-value

1-tail p-value \tabularnewline Gini[t]

0.483336

0.467912

1.032965

0.31459

0.157295 \tabularnewline Pobreza[t]

0.79615

0.294906

2.699669

0.014199

0.0071 \tabularnewline Constant

-27.935853

16.448553

-1.698378

0.105754

0.052877 \tabularnewline \tabularnewline

Variable

Elasticity

S.E.^*

T-STATH0: |elast| = 1

2-tail p-value

1-tail p-value \tabularnewline %Gini[t]

0.902649

0.873843

-0.111405

0.912463

0.456232 \tabularnewline %Pobreza[t]

1.078182

0.399376

0.19576

0.846876

0.423438 \tabularnewline %Constant

-0.980831

0.577511

-0.033192

0.973867

0.486934 \tabularnewline

Variable

Stand. Coeff.

S.E.^*

T-STATH0: coeff = 0

2-tail p-value

1-tail p-value \tabularnewline S-Gini[t]

0.244045

0.236257

1.032965

0.31459

0.157295 \tabularnewline S-Pobreza[t]

0.637816

0.236257

2.699669

0.014199

0.0071 \tabularnewline S-Constant

0.5 \tabularnewline ^*Note

computed against deterministic endogenous series \tabularnewline

Variable

Partial Correlation \tabularnewline Gini[t]

0.230592 \tabularnewline Pobreza[t]

0.526538 \tabularnewline Constant

-0.36305 \tabularnewline Critical Values (alpha = 5%) \tabularnewline 1-tail CV at 5%

1.73 \tabularnewline 2-tail CV at 5%

2.09 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=235230&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]Gini[t][/C]

0.483336[/C]

0.467912[/C]

1.032965[/C]

0.31459[/C]

0.157295[/C][/ROW] [ROW][C]Pobreza[t][/C]

0.79615[/C]

0.294906[/C]

2.699669[/C]

0.014199[/C]

0.0071[/C][/ROW] [ROW][C]Constant[/C]

-27.935853[/C]

16.448553[/C]

-1.698378[/C]

0.105754[/C]

0.052877[/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]%Gini[t][/C]

0.902649[/C]

0.873843[/C]

-0.111405[/C]

0.912463[/C]

0.456232[/C][/ROW] [ROW][C]%Pobreza[t][/C]

1.078182[/C]

0.399376[/C]

0.19576[/C]

0.846876[/C]

0.423438[/C][/ROW] [ROW][C]%Constant[/C]

-0.980831[/C]

0.577511[/C]

-0.033192[/C]

0.973867[/C]

0.486934[/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-Gini[t][/C]

0.244045[/C]

0.236257[/C]

1.032965[/C]

0.31459[/C]

0.157295[/C][/ROW] [ROW][C]S-Pobreza[t][/C]

0.637816[/C]

0.236257[/C]

2.699669[/C]

0.014199[/C]

0.0071[/C][/ROW] [ROW][C]S-Constant[/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]Gini[t][/C]

0.230592[/C][/ROW] [ROW][C]Pobreza[t][/C]

0.526538[/C][/ROW] [ROW][C]Constant[/C]

-0.36305[/C][/ROW] [ROW][C]Critical Values (alpha = 5%)[/C][/ROW] [ROW][C]1-tail CV at 5%[/C]

1.73[/C][/ROW] [ROW][C]2-tail CV at 5%[/C]

2.09[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=235230&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235230&T=1

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.E.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
Gini[t]	0.483336	0.467912	1.032965	0.31459	0.157295
Pobreza[t]	0.79615	0.294906	2.699669	0.014199	0.0071
Constant	-27.935853	16.448553	-1.698378	0.105754	0.052877

Variable	Elasticity	S.E.^*	T-STATH0: \|elast\| = 1	2-tail p-value	1-tail p-value
%Gini[t]	0.902649	0.873843	-0.111405	0.912463	0.456232
%Pobreza[t]	1.078182	0.399376	0.19576	0.846876	0.423438
%Constant	-0.980831	0.577511	-0.033192	0.973867	0.486934
Variable	Stand. Coeff.	S.E.^*	T-STATH0: coeff = 0	2-tail p-value	1-tail p-value
S-Gini[t]	0.244045	0.236257	1.032965	0.31459	0.157295
S-Pobreza[t]	0.637816	0.236257	2.699669	0.014199	0.0071
S-Constant	0	0	0	1	0.5
^*Note	computed against deterministic endogenous series
Variable	Partial Correlation
Gini[t]	0.230592
Pobreza[t]	0.526538
Constant	-0.36305
Critical Values (alpha = 5%)
1-tail CV at 5%	1.73
2-tail CV at 5%	2.09

Multiple Linear Regression - Regression Statistics
Multiple R	0.858019
R-squared	0.736196
Adjusted R-squared	0.708427
F-TEST	26.511552
Observations	22
Degrees of Freedom	19
Multiple Linear Regression - Residual Statistics
Standard Error	16.573635
Sum Squared Errors	5219.021958
Log Likelihood	-91.375899
Durbin-Watson	1.797493
Von Neumann Ratio	1.883088
# e[t] > 0	8
# e[t] < 0	14
# Runs	10
Runs Statistic	-0.560123

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Regression Statistics \tabularnewline

Multiple R

0.858019 \tabularnewline R-squared

0.736196 \tabularnewline Adjusted R-squared

0.708427 \tabularnewline F-TEST

26.511552 \tabularnewline Observations

22 \tabularnewline Degrees of Freedom

19 \tabularnewline Multiple Linear Regression - Residual Statistics \tabularnewline Standard Error

16.573635 \tabularnewline Sum Squared Errors

5219.021958 \tabularnewline Log Likelihood

-91.375899 \tabularnewline Durbin-Watson

1.797493 \tabularnewline Von Neumann Ratio

1.883088 \tabularnewline # e[t] > 0

8 \tabularnewline # e[t] < 0

14 \tabularnewline # Runs

10 \tabularnewline Runs Statistic

-0.560123 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=235230&T=2

[TABLE]

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

[ROW][C]Multiple R[/C]

0.858019[/C][/ROW] [ROW][C]R-squared[/C]

0.736196[/C][/ROW] [ROW][C]Adjusted R-squared[/C]

0.708427[/C][/ROW] [ROW][C]F-TEST[/C]

26.511552[/C][/ROW] [ROW][C]Observations[/C]

22[/C][/ROW] [ROW][C]Degrees of Freedom[/C]

19[/C][/ROW] [ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW] [ROW][C]Standard Error[/C]

16.573635[/C][/ROW] [ROW][C]Sum Squared Errors[/C]

5219.021958[/C][/ROW] [ROW][C]Log Likelihood[/C]

-91.375899[/C][/ROW] [ROW][C]Durbin-Watson[/C]

1.797493[/C][/ROW] [ROW][C]Von Neumann Ratio[/C]

1.883088[/C][/ROW] [ROW][C]# e[t] > 0[/C]

8[/C][/ROW] [ROW][C]# e[t] < 0[/C]

14[/C][/ROW] [ROW][C]# Runs[/C]

10[/C][/ROW] [ROW][C]Runs Statistic[/C]

-0.560123[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=235230&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235230&T=2

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Regression Statistics
Multiple R	0.858019
R-squared	0.736196
Adjusted R-squared	0.708427
F-TEST	26.511552
Observations	22
Degrees of Freedom	19
Multiple Linear Regression - Residual Statistics
Standard Error	16.573635
Sum Squared Errors	5219.021958
Log Likelihood	-91.375899
Durbin-Watson	1.797493
Von Neumann Ratio	1.883088
# e[t] > 0	8
# e[t] < 0	14
# Runs	10
Runs Statistic	-0.560123

Multiple Linear Regression - Ad Hoc Selection Test Statistics
Akaike (1969) Final Prediction Error	312.142462
Akaike (1973) Log Information Criterion	5.74175
Akaike (1974) Information Criterion	311.609287
Schwarz (1978) Log Criterion	5.890529
Schwarz (1978) Criterion	361.596386
Craven-Wahba (1979) Generalized Cross Validation	318.05674
Hannan-Quinn (1979) Criterion	322.724127
Rice (1984) Criterion	326.188872
Shibata (1981) Criterion	301.92689

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Ad Hoc Selection Test Statistics \tabularnewline

Akaike (1969) Final Prediction Error

312.142462 \tabularnewline Akaike (1973) Log Information Criterion

5.74175 \tabularnewline Akaike (1974) Information Criterion

311.609287 \tabularnewline Schwarz (1978) Log Criterion

5.890529 \tabularnewline Schwarz (1978) Criterion

361.596386 \tabularnewline Craven-Wahba (1979) Generalized Cross Validation

318.05674 \tabularnewline Hannan-Quinn (1979) Criterion

322.724127 \tabularnewline Rice (1984) Criterion

326.188872 \tabularnewline Shibata (1981) Criterion

301.92689 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=235230&T=3

[TABLE]

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

[ROW][C]Akaike (1969) Final Prediction Error[/C]

312.142462[/C][/ROW] [ROW][C]Akaike (1973) Log Information Criterion[/C]

5.74175[/C][/ROW] [ROW][C]Akaike (1974) Information Criterion[/C]

311.609287[/C][/ROW] [ROW][C]Schwarz (1978) Log Criterion[/C]

5.890529[/C][/ROW] [ROW][C]Schwarz (1978) Criterion[/C]

361.596386[/C][/ROW] [ROW][C]Craven-Wahba (1979) Generalized Cross Validation[/C]

318.05674[/C][/ROW] [ROW][C]Hannan-Quinn (1979) Criterion[/C]

322.724127[/C][/ROW] [ROW][C]Rice (1984) Criterion[/C]

326.188872[/C][/ROW] [ROW][C]Shibata (1981) Criterion[/C]

301.92689[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=235230&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235230&T=3

As an alternative you can also use a 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 Error	312.142462
Akaike (1973) Log Information Criterion	5.74175
Akaike (1974) Information Criterion	311.609287
Schwarz (1978) Log Criterion	5.890529
Schwarz (1978) Criterion	361.596386
Craven-Wahba (1979) Generalized Cross Validation	318.05674
Hannan-Quinn (1979) Criterion	322.724127
Rice (1984) Criterion	326.188872
Shibata (1981) Criterion	301.92689

Multiple Linear Regression - Analysis of Variance
ANOVA	DF	Sum of Squares	Mean Square
Regression	2	14564.67077	7282.335385
Residual	19	5219.021958	274.685366
Total	21	19783.692727	942.08060606061
F-TEST	26.511552
p-value	3.0E-6

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Analysis of Variance \tabularnewline

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

Regression

14564.67077

7282.335385 \tabularnewline Residual

5219.021958

274.685366 \tabularnewline Total

19783.692727

942.08060606061 \tabularnewline F-TEST

26.511552 \tabularnewline p-value

3.0E-6 \tabularnewline

\hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=235230&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]

2[/C]

14564.67077[/C]

7282.335385[/C][/ROW] [ROW][C]Residual[/C]

19[/C]

5219.021958[/C]

274.685366[/C][/ROW] [ROW][C]Total[/C]

21[/C]

19783.692727[/C]

942.08060606061[/C][/ROW] [ROW][C]F-TEST[/C]

26.511552[/C][/ROW] [ROW][C]p-value[/C]

3.0E-6[/C][/ROW]

[/TABLE] Source: https://freestatistics.org/blog/index.php?pk=235230&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235230&T=4

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Analysis of Variance
ANOVA	DF	Sum of Squares	Mean Square
Regression	2	14564.67077	7282.335385
Residual	19	5219.021958	274.685366
Total	21	19783.692727	942.08060606061
F-TEST	26.511552
p-value	3.0E-6

Parameters (Session):

Parameters (R input):

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

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Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code