Aula8

importa dados

#Teste de hipóteses (Teste T)

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

library(readxl)

mg<- read_excel("C:dados-diversos.xlsx")

mg |> 
  ggplot(aes(trat, comp))+
  geom_jitter(width =0.05)+
  geom_boxplot(fill = NA, 
               outlier.colour = NA)+
  ylim(5, 20)+
  annotate(geom = "text",
           x = 0.7, y = 19,
           label = "t = 8.12; P < 0.001;")

mg |> 
  
  ggplot(aes(trat, comp))+
  stat_summary(fun.data = "mean_se")

mg2 <- mg |> 
  pivot_wider(1, 
              names_from = trat,
              values_from = comp)

Warning: Specifying the `id_cols` argument by position was deprecated in tidyr 1.3.0.
ℹ Please explicitly name `id_cols`, like `id_cols = 1`.

t <- t.test(mg2$Mg2, mg2$control)
t

    Welch Two Sample t-test

data:  mg2$Mg2 and mg2$control
t = -8.1549, df = 17.354, p-value = 2.423e-07
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -6.490393 -3.825607
sample estimates:
mean of x mean of y 
   10.520    15.678 

library(report)

Warning: package 'report' was built under R version 4.2.3

report(t)

Effect sizes were labelled following Cohen's (1988) recommendations.

The Welch Two Sample t-test testing the difference between mg2$Mg2 and
mg2$control (mean of x = 10.52, mean of y = 15.68) suggests that the effect is
negative, statistically significant, and large (difference = -5.16, 95% CI
[-6.49, -3.83], t(17.35) = -8.15, p < .001; Cohen's d = -3.65, 95% CI [-5.12,
-2.14])

Using the infer package

library(infer)

Warning: package 'infer' was built under R version 4.2.3

mg |> 
  t_test(comp ~ trat,
         order = c("control", "Mg2"))

# A tibble: 1 × 7
  statistic  t_df     p_value alternative estimate lower_ci upper_ci
      <dbl> <dbl>       <dbl> <chr>          <dbl>    <dbl>    <dbl>
1      8.15  17.4 0.000000242 two.sided       5.16     3.83     6.49

https://www.datanovia.com/en/lessons/t-test-in-r/