Correlation

Correlation in graphs http://access-excel.tips/wp-content/uploads/2015/06/Correlation-Levels.gif Correlation in formulas Resultado de imagen de correlation formula Resultado de imagen de correlation formula covariance Resultado de imagen de correlation formula Resultado de imagen de correlation formula Example: Icecream sales and temperature correlation Student’s t test (signal/noise ratio) with N-2 degrees of freedom Resultado de imagen de correlation formula t What is correlation in simple words? Another example to explain correlation is not causation. Resultado de imagen de correlation Resultado de imagen de correlation It is very important to draw data in graphs because correlation and other data could be the same (mean, variance, linear relationship), but the data could be very different as in the Anscombe’s quartet. Linear model > lm(formula=NO2~NO,data=martorell) Call: lm(formula = NO2 ~ NO, data = martorell) Coefficients: (Intercept) NO 29.1185 0.3177
lmfit<-lm(formula=NO2~NO,data=martorell) > plot(lmfit) Hit <Return> to see next plot: lmfit1 plot(martorell$NO, martorell$NO2) > abline(lmfit) abline
This means that the linear relation is NO2=29.1185+0.3177NO If you ask for summary(lmfit) you will obtain all this information: > summary(lmfit) Call: lm(formula = NO2 ~ NO, data = martorell) Residuals: Min 1Q Median 3Q Max -49.453 -12.389 -1.978 9.845 84.116 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 29.118529 0.216955 134.21 <2e-16 *** NO 0.317714 0.004818 65.94 <2e-16 *** — Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 16.17 on 8242 degrees of freedom (540 observations deleted due to missingness) Multiple R-squared: 0.3454, Adjusted R-squared: 0.3453 F-statistic: 4348 on 1 and 8242 DF, p-value: < 2.2e-16 Correlation tests in R R CODE > cor.test(martorell$NO,martorell$NO2) Pearson’s product-moment correlation data: martorell$NO and martorell$NO2 t = 65.942, df = 8242, p-value < 2.2e-16 alternative hypothesis: true correlation is not equal to 0 95 percent confidence interval: 0.5733714 0.6016387 sample estimates: cor 0.5876844 This means correlation is 0.59 Corrplot R library allows you to graph different correlation coefficients between pollutants corrplot1 correlation  

The best way to predict the future is to invent it (Alan Kay)