In npalmer11/psyc7709:

knitr::opts_chunk$set(echo = TRUE)

1.Use R to conduct a t.test and ANOVA on this data. Then use R to prove that the results of both analyses are the same. For example, prove that the p-values are the same, and prove that the F-value and T-value are related. (3 points)

library(tibble)
example_data <- tibble(Group = rep(c("A","B"), each = 5),
                       DV = c(2,4,3,5,4,7,6,5,6,7))


t_test <- t.test(DV~Group, var.equal=TRUE, data = example_data)
my_aov <- summary(aov(DV~Group, data = example_data))

t_test$p.value
my_aov[[1]]$`Pr(>F)`[1]

round(t_test$p.value, digits=5) == round(my_aov[[1]]$`Pr(>F)`[1],digits=5)

t_test$statistic
my_aov[[1]]$`F value`[1]

t_test$statistic^2 == my_aov[[1]]$`F value`[1]

t_test$statistic^2
my_aov[[1]]$`F value`[1]

round(t_test$statistic^2, digits = 1) == round(my_aov[[1]]$`F value`[1], digits = 1)

1. Look at the lab on ANOVA that I wrote for our undergraduate statistics OER lab manual https://crumplab.github.io/statisticsLab/lab-8-one-way-anova.html. That lab shows an example of obtaining data from a published paper in psych science where a one-factor ANOVA was used as a part of the analysis. Load the data, conduct the ANOVA, report a ggplot of the means, and use papaja to help you write a short results section reporting the ANOVA result. (3 points).

library(data.table)
library(readr)

Jamesetal2015Experiment2 <- read_csv("data/Jamesetal2015Experiment2.csv")
View(Jamesetal2015Experiment2)

all_data <- fread("data/Jamesetal2015Experiment2.csv")


# re-labeling
all_data$Condition <- as.factor(all_data$Condition)
levels(all_data$Condition) <- c("Control",
                                "Reactivation+Tetris", 
                                "Tetris_only",
                                "Reactivation_only") 

library(ggplot2)
ggplot(all_data, aes(x=Condition, y=Days_One_to_Seven_Number_of_Intrusions))+
  geom_bar(stat="summary", fun= "mean", position = "dodge")+
  geom_point()


my_aov <- aov(Days_One_to_Seven_Number_of_Intrusions~Condition, data = all_data)

summary(my_aov)

library(papaja)
apa_print(my_aov)$full_result$Condition

A one-factor between-subjects ANOVA was used to examine the average for intrusive memories for the week from participants in each condition. The independent variables consisted of the intervention type of (no-task control, reactivation plus tetris, reactivation alone, and tetris alone). From the ANOVA performed, we found a main effect of Intervention type, r apa_print(my_aov)$full_result$Condition.

npalmer11/psyc7709 documentation built on June 3, 2022, 7:04 a.m.