Regresión Lineal Simple RS1. Plantas de Tratamiento de agua, DF , 1998 Planta Cap Vol Rosario 25 567.65 Coyoacán 400 5676.48 Acueducto de 87 1923.7 Guadalupe San Juan de Aragón 500 4446.58 Ciudad Deportiva 230 4099.68 Iztacalco 13 315.36 Cerro de la Estrella 4000 46957.1 San Pedro Atocpan 60 1103.76 San Juan Ixtayopan 15 252.29 San Andrés Mixquic 30 946.08 Abasolo 15 157.68 Heroico Colegio Militar 30 630.72 Parres 7 31.54 PEMEX 26 315.36 Xicalco 7 94.6 Reclusorio Sur 30 378.43 San Luis Tlaxialtemalco 150 1892.16 Tlatelolco 22 378.43 Bosque de las Lomas 55 473.04 Campo Militar No. 1 30 378.43 Chapultepec 160 2018.3 summary(modelo) Call: lm(formula = Vol ~ Cap) Residuals: Min 1Q -1593.94 -188.53 Median -60.96 3Q 78.99 Max 1212.30 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 201.3821 126.8122 1.588 0.129 Cap 11.6783 0.1429 81.707 <2e-16 *** --Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 551.3 on 19 degrees of freedom Multiple R-squared: 0.9972, Adjusted R-squared: 0.997 F-statistic: 6676 on 1 and 19 DF, p-value: < 2.2e-16 anova(modelo) Analysis of Variance Table Response: Vol Df Sum Sq Cap 1 2029113094 Residuals 19 5774809 Mean Sq 2029113094 303937 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 F value 6676.1 Pr(>F) < 2.2e-16 *** shapiro.test(modelo$residual) Shapiro-Wilk normality test data: modelo$residual W = 0.8475, p-value =0.003846 Transformación de variable y<-sqrt(Vol) m2<-lm(y~Cap) Analysis of Variance Table Response: y Df Sum Sq Cap 1 36673 Residuals 19 3768 Mean Sq 36673 198 F value 184.94 Pr(>F) 3.047e-11 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Shapiro-Wilk normality test data: m2$residuals W = 0.9196, p-value = 0.08506 RS2. Modelo de Pinzones summary(m) Call: lm(formula = beak.length ~ mass, data = KenyaFinches) Residuals: Min 1Q Median -1.05373 -0.27044 -0.05373 Coefficients: Estimate Std. (Intercept) 6.487159 mass 0.110411 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 Error 0.112906 0.004608 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 3Q 0.33806 t 57.46 23.96 Max 0.82956 value Pr(>|t|) <2e-16 *** <2e-16 *** Residual standard error: 0.4174 on 43 degrees of freedom Multiple R-squared: 0.9303, Adjusted R-squared: 0.9287 F-statistic: 574 on 1 and 43 DF, p-value: < 2.2e-16 > Schluter, D. 1988. The evolution of finch communities on islands and continents: Kenya vs. Galapagos. Ecological Monographs 58: 229-249. anova(m) Analysis of Variance Table Response: beak.length Df Sum Sq Mass 1 100.000 Residuals 43 7.491 --- Signif. codes: 0 ‘***’ 0.001 Mean Sq F value Pr(>F) 100.000 574.03 < 2.2e-16 *** 0.174 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 shapiro.test(m$residuals) Shapiro-Wilk normality test data: m$residuals W = 0.9784, p-value = 0.5572 RS3. Reforestación en el DF m<-lm(Reforestacion~Superfice) summary(m) Call: lm(formula = Reforestacion ~ Superfice) Residuals: Min 1Q Median 3Q Max -148.43 -97.75 -10.08 92.44 180.59 Coefficients: Estimate Std. Error t (Intercept) 186.3801 42.2576 4.411 Superfice -0.3078 0.3439 -0.895 value Pr(>|t|) 0.000593 *** 0.385911 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 111.4 on 14 degrees of freedom Multiple R-squared: 0.05412, Adjusted R-squared: -0.01344 F-statistic: 0.801 on 1 and 14 DF, p-value: 0.3859 anova(m) Analysis of Variance Table Response: Reforestacion Df Sum Sq Superfice 1 9943 Residuals 14 173778 Mean Sq 9943.1 12412.7 F value 0.801 Pr(>F) 0.3859 RS4. Dióxido de Carbono por uso vehicular Año base 1970=100 Redfern, A., Bunyan, M., and Lawrence, T. (eds) (2003). The Environment in Your Pocket, 7th edn. London: UK Department for Environment, Food and Rural Affairs. anio 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 co2 104.619 109.785 117.197 114.404 111.994 116.898 119.915 126.07 128.759 130.196 126.409 103.136 134.212 140.721 143.462 153.074 159.999 170.312 177.51 182.686 181.348 183.757 185.869 186.872 185.1 192.249 194.667 193.438 uso 105.742 110.995 116.742 114.592 115.605 121.467 123.123 127.953 127.648 135.66 138.139 141.911 143.707 151.205 154.487 162.285 174.837 187.403 202.985 204.959 205.325 205.598 205.641 210.826 214.947 220.753 225.742 229.027 Call: lm(formula = co2 ~ uso) Residuals: Min 1Q -29.5946 -0.7761 Coefficients: Estimate (Intercept) 25.39475 uso 0.75636 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 Median 1.0901 3Q 2.4873 Std. Error 5.05584 0.02999 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 t 5.023 25.223 Max 6.8163 value Pr(>|t|) 3.16e-05 *** < 2e-16 *** Residual standard error: 6.503 on 26 degrees of freedom Multiple R-squared: 0.9607, Adjusted R-squared: 0.9592 F-statistic: 636.2 on 1 and 26 DF, p-value: < 2.2e-16 Analysis of Variance Table Response: co2 Df Sum Sq Uso 1 26904.1 Residuals 26 1099.5 --- Signif. codes: 0 ‘***’ 0.001 Mean Sq F value Pr(>F) 26904.1 636.21 < 2.2e-16 *** 42.3 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1