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| summary(aov(Y~diamonds$price)) | |
| Response 1 : | |
| Df Sum Sq Mean Sq F value Pr(>F) | |
| diamonds$price 1 53093 53093 193740 < 2.2e-16 *** | |
| Residuals 53938 14781 0 | |
| --- | |
| Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 | |
| Response 2 : | |
| Df Sum Sq Mean Sq F value Pr(>F) |
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| Y <- cbind(diamonds$x, diamonds$y, diamonds$z) | |
| mx<-manova(Y~diamonds$price) | |
| summary(mx) | |
| Df Pillai approx F num Df den Df Pr(>F) | |
| diamonds$price 1 0.78254 64698 3 53936 < 2.2e-16 *** | |
| Residuals 53938 |
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| library(ggplot2) | |
| data("diamonds") | |
| head(diamonds) | |
| # A tibble: 6 x 10 | |
| carat cut color clarity depth table price x y z | |
| <dbl> <ord> <ord> <ord> <dbl> <dbl> <int> <dbl> <dbl> <dbl> | |
| 1 0.23 Ideal E SI2 61.5 55 326 3.95 3.98 2.43 | |
| 2 0.21 Premium E SI1 59.8 61 326 3.89 3.84 2.31 | |
| 3 0.23 Good E VS1 56.9 65 327 4.05 4.07 2.31 | |
| 4 0.290 Premium I VS2 62.4 58 334 4.2 4.23 2.63 |
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| var.test(formula = Ozone ~ Month, data = airquality, subset= Month %in% c("5","6")) | |
| F test to compare two variances | |
| data: Ozone by Month | |
| F = 1.4898, num df = 25, denom df = 8, p-value = 0.5765 | |
| alternative hypothesis: true ratio of variances is not equal to 1 | |
| 95 percent confidence interval: | |
| 0.378455 4.101711 | |
| sample estimates: |
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| var.test(formula = Ozone ~ Month, data = airquality) | |
| Error in var.test.formula(formula = Ozone ~ Month, data = airquality) : | |
| fator de agrupamento deve ter exatamente 2 níveis |
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| library(datasets) | |
| data(airquality) | |
| names(airquality) | |
| [1] "Ozone" "Solar.R" "Wind" "Temp" "Month" "Day" |
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| setwd("..") | |
| install("cats") |
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| document() |
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| #' Diagnóstico do modelo | |
| #' Função criar gráficos de modelos GLM para diagnóstico | |
| #' Para utilizar: modeldiag() |
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| create("rutils") |
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