Richelle - Worksheet 1

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library(tidyverse)
library(mosaic)
library(ggplot2)
library(moments)
library(PB130)
library(sjlabelled)
library(Hmisc)

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WVS <- readRDS("~/Desktop/PB130-master/MT4/Workshop/WV6_Data_R_v20180912.rds")
WVS$V2A <- as_character(WVS$V2A)

WVSLifeSatisfaction <- 
  WVS %>%
  select(V2A,V23)

favstats(~V23,  data = WVSLifeSatisfaction)

PB130(WVSLifeSatisfaction$V23)

           estimate          se         Z
skew     -0.7579698 0.008184633 -92.60890
kurtosis  0.4220976 0.016369082  25.78627

#Reflection: The -0.758 skew shows that it is negative skewed as the mean is pulled to the negative end and that on a scale of 2-9, the mean (6.54) shows that Algerians, on average, have medium to high life satisfaction. The sd of 1.79 shows that the data is not too dispersed. The kurtosis of 0.4220976 suggests that the life satisfaction in Algeria follows a normal distribution.

WVSLifeSatisfaction %>% 
  ggplot(aes(x= V23)) +
  geom_histogram(aes(y=..density..), binwidth=.4, colour="black", fill="white") + 
  geom_density(adjust = 4, alpha = .2, fill = "antiquewhite3") +
  geom_vline(aes(xintercept=mean(V23)), col="black", linetype="dashed", size=1) + 
 ylab("Number of Responses") +
  xlab("Life Satisfaction Score in Algeria")+
  ggtitle ("Life Satisfaction in Algeria in the WVS")

  theme_minimal(base_size = 8) 

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Reflection on Histogram

The graph confirmed the negative skewness of the data as the mean is pulled towards the left. However, it doesn’t seem to follow the perfect normal distribution as the life satisfaction score is clustered from 5-10 but doesn’t show level off to the right.

#Boxplots

WVSLifeSatisfaction %>%
  ggplot(aes(x= factor(1), y = V23)) + 
  geom_boxplot(width = 0.3, fill = "white") +
  geom_jitter(aes(color = as.factor(V23), shape = as.factor(V23)), width = 0.1, size = 1) + 
  stat_summary(fun.y = mean, geom = "point", shape = 18, size = 2.5, color ="red") +
  xlab(NULL) +
  ggtitle("Box-Plots for life satisfaction in Algeria") +
  theme_minimal(base_size = 8) +
  theme(legend.title=element_blank())

#Reflection As shown in the box plot, the mean (as indicated by the red dot) is negatively skewed and lower than the median, which has been corroborated by the data.

#Overall life satisfaction

WVSsummary <- 
  WVSLifeSatisfaction %>%
  group_by(V2A) %>% 
  summarise(meanlifesat = mean (V23))
head(WVSsummary)

WVSsummary %>% 
  ggplot(aes(x = reorder(V2A, meanlifesat), y = meanlifesat)) + 
  geom_point() + 
  theme(axis.text.x = element_text(angle = 90, hjust = .5), text = element_text(size = 8)) + 
  xlab("Country") + 
  ylab("Mean Reported Life Satisfaction Value") + 
  labs(title = "Self-reported Life Satisfaction", 
       subtitle = "Source: World Values Survey, Wave 6, 2010-14")

#Reflection Which country has the highest life satisfaction? Mexico Which country has the lowest life satisfaction? Egypt