library(readxl)
library(tidyverse)
Warning: package 'ggplot2' was built under R version 4.2.3
Warning: package 'tibble' was built under R version 4.2.3
Warning: package 'dplyr' was built under R version 4.2.3
── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr 1.1.2 ✔ readr 2.1.4
✔ forcats 1.0.0 ✔ stringr 1.5.0
✔ ggplot2 3.4.2 ✔ tibble 3.2.1
✔ lubridate 1.9.2 ✔ tidyr 1.3.0
✔ purrr 1.0.1
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
estande <- read_excel("dados-diversos.xlsx", "estande")
estande |>
ggplot(aes(trat, nplants, group = exp))+
geom_point()+
facet_wrap(~exp)+
ylim(0,max(estande$nplants))+
geom_smooth(se = F)
`geom_smooth()` using method = 'loess' and formula = 'y ~ x'
Warning: package 'ggtext' was built under R version 4.2.3
estande2 <- estande |>
filter(exp == 2)|>
group_by(trat) |>
summarise(mean_nplants = mean(nplants))
estande2 |>
ggplot(aes(trat, mean_nplants))+
geom_point()+
#geom_line()+
geom_smooth(se = F, formula = y ~ poly(x, 2), method = "lm", color = "black")+
theme_minimal()+
annotate(geom = "text",
x = 25, y = 70,
label = "y = 66.3 - 1.777x + 0.0222x2
R2 = 0.88")
estande2 <- estande2 |>
mutate(trat2 = trat^2)
m1 <- lm(mean_nplants ~ trat,
data = estande2)
summary(m1)
Call:
lm(formula = mean_nplants ~ trat, data = estande2)
Residuals:
1 2 3 4 5 6
12.764 -2.134 -6.782 -3.327 -4.669 4.147
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 60.9857 4.5505 13.402 0.000179 ***
trat -0.7007 0.2012 -3.483 0.025294 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 8.117 on 4 degrees of freedom
Multiple R-squared: 0.752, Adjusted R-squared: 0.69
F-statistic: 12.13 on 1 and 4 DF, p-value: 0.02529
m2 <- lm(mean_nplants ~ trat + trat2,
data = estande2)
summary(m2)
Call:
lm(formula = mean_nplants ~ trat + trat2, data = estande2)
Residuals:
1 2 3 4 5 6
7.4484 -4.4200 -6.4386 1.0739 3.0474 -0.7111
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 66.30156 4.70800 14.083 0.000776 ***
trat -1.77720 0.62263 -2.854 0.064878 .
trat2 0.02223 0.01242 1.790 0.171344
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.517 on 3 degrees of freedom
Multiple R-squared: 0.8801, Adjusted R-squared: 0.8001
F-statistic: 11.01 on 2 and 3 DF, p-value: 0.04152
df AIC
m1 3 45.72200
m2 4 43.36151
