2 CHAPTER 1: INTRODUCTION

2.1 Screenshot 1.4 Summary statistics for a series (Page 20)

library(foreign)
library(moments)

data <- read.dta("Dataset/ukhp.dta")
data$Date <- seq(1991 + 1/12, 2013 + 5/12, by = 1/12)
data <- na.omit(data)
head(data)

##   Month       HP        dhp dhpf_stat  dhpf_dyn   dhpf_smo     Date
## 2   373 53496.80  0.8389505 0.4626106 0.4626106 0.37499204 1991.167
## 3   374 52892.86 -1.1289220 0.5956236 0.5956236 0.48623425 1991.250
## 4   375 53677.44  1.4833262 0.2403217 0.2403217 0.09897207 1991.333
## 5   376 54385.73  1.3195330 0.1158991 0.1158991 0.43089539 1991.417
## 6   377 55107.38  1.3269076 1.0256131 1.0256131 0.64396191 1991.500
## 7   378 54541.12 -1.0275464 0.9679196 0.9679196 0.80771017 1991.583

Histogram of House Price Changes

par(mar = c(4,4,2,1), mgp = c(2,0.5,0))
hist(data$dhp, breaks = 26, freq = TRUE, las = 1,
     col = "steelblue4", xlim = c(-4,4), ylim = c(0,25),
     xlab = "House Price Changes", ylab = "Frequency", main = "Histogram of House Price Changes")
box()

Descriptive Statistics

statistics <- list(
  Mean = mean(data$dhp),
  Median = median(data$dhp),
  Max = max(data$dhp),
  Min = min(data$dhp),
  SD = sd(data$dhp),
  Skewness = skewness(data$dhp),
  Kurtosis = kurtosis(data$dhp),
  Jarque_Bera_Test = jarque.test(data$dhp)
)

statistics

## $Mean
## [1] 0.4379951
## 
## $Median
## [1] 0.4941616
## 
## $Max
## [1] 3.802188
## 
## $Min
## [1] -3.404716
## 
## $SD
## [1] 1.200502
## 
## $Skewness
## [1] -0.1083071
## 
## $Kurtosis
## [1] 3.275901
## 
## $Jarque_Bera_Test
## 
##  Jarque-Bera Normality Test
## 
## data:  data$dhp
## JB = 1.374, p-value = 0.5031
## alternative hypothesis: greater

2.2 Screenshot 1.5. A line graph (Page 21)

par(mar = c(4,4,2,1), mgp = c(2,0.5,0))
plot(data$Date, data$HP, type = "l", las = 1, col = "steelblue4",
     xlab = "Year", ylab = "Average House Price",
     main = "Average House Price Over Time", ylim = c(40000, 200000))