Regresion
Correlación lineal
Primero mostraremos la salida del programa SPSS y luego con esto realizaremos el análisiscorrespondiente.
• Estadísticas descriptivas
Descriptive Statistics
Mean Std. Deviation N
PIB 94518,7333 36941,96677 15
IP 662,9333 154,53870 15
• Correlación lineal de Pearson
CorrelationsPIB IP
PIB Pearson Correlation 1 ,870**
Sig. (2-tailed) ,000
N 15 15
IP Pearson Correlation ,870** 1
Sig. (2-tailed) ,000
N 15 15
**. Correlation is significant at the 0.01 level(2-tailed).
• Correlación lineal de Kendall's tau_b
Correlations
PIB IP
Kendall's tau_b PIB Correlation Coefficient 1,000 ,746**
Sig. (2-tailed) . ,000
N 15 15
IP Correlation Coefficient,746** 1,000
Sig. (2-tailed) ,000 .
N 15 15
**. Correlation is significant at the 0.01 level (2-tailed).
• Correlacion lineal de Spearman's rho
Correlations
PIB IP
Spearman's rhoPIB Correlation Coefficient 1,000 ,890**
Sig. (2-tailed) . ,000
N 15 15
IP Correlation Coefficient ,890** 1,000
Sig. (2-tailed) ,000 .
N 15 15
**. Correlation is significant at the 0.01level (2-tailed).
Regresión Lineal Simple
• Resumen del modelo
Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 ,870a ,758 ,739 78,96135
a. Predictors:(Constant), PIB
• Análisis de la varianza
ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression 253297,305 1 253297,305 40,626 ,000a
Residual 81053,628 13 6234,894
Total 334350,933...
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