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Discussion : Running Head

Based on Jonathan Wolff’s analysis of the ideas of Plato, Rousseau, and Mill in his (Wolff, 2016) Chapter 3, each thinker addressed some problems with democratic voting, understood as simple majority rule. (i) Explain what these problems are, and (ii) discuss whether you think that Fishkin’s ideas in (Simon, 2002:230-233) can help solve these problems. Continue reading

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R Task on ANOVA Model

rm(list = ls())
options(warn = -1)
library(readxl)

## Reading the data from excel
Project_2_Data <- read_excel(“Stat 481 Project 2 Data.xls”)
str(Project_2_Data)

## Cleaning and attributing the dtaa
Project_2_Data$courses = as.factor(Project_2_Data$courses)
Project_2_Data$gender = as.factor(Project_2_Data$gender)
levels(Project_2_Data$gender) <- c(“Female”, “Male”)
levels(Project_2_Data$courses) <- c(“Algebra”, “Algebra&Geometry”, “Calculus”)

attach(Project_2_Data)

## Descriptives
library(ggplot2)
library(hrbrthemes)
library(dplyr)
library(tidyr)
library(viridis)
temp = aggregate(score~courses+gender, Project_2_Data, FUN = mean)

qqnorm(score)
ggplot(Project_2_Data, aes(x = score)) + geom_histogram()

summary(Project_2_Data)
p1 <- ggplot(data=Project_2_Data, aes(x=score, fill=courses)) + geom_density(adjust=1.5, alpha=.4) + theme_ipsum()

p2 <- ggplot(data=Project_2_Data, aes(x=score, fill=gender)) + geom_density(adjust=1.5, alpha=.4) + theme_ipsum()
## Model
## Test of normality and other assumptions
ks.test(score, pnorm, mean = mean(score), sd= sd(score))
bartlett.test(score~courses, data = Project_2_Data)
bartlett.test(score~gender, data = Project_2_Data)

## Linear model
model1 = anova(score ~ courses + gender, data = Project_2_Data)
model1
summary(model1)
## Post Hoc
library(DescTools)
PostHocTest(model1, method = “bonferroni”)
PostHocTest(model1, method = “hsd”)