Assignment submission

Q1Script.R

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+library('ggplot2')
+
+data <- read.table(file = 'StockData.txt',header=TRUE)
+
+plot <- ggplot(data, aes(x = AAPL,y = S.P)) +
+          geom_point() +
+          xlab('AAPL Daily Return') +
+          ylab('S&P Daily Return') +
+          stat_smooth(method = 'lm') +
+          labs(title = 'Daily Returns of AAPL and S&P500') +
+          theme_classic()
+
+ggsave('Q1_plot1.jpg', plot = plot, width = 12, height = 8, dpi = 500)
+

Q2Script.R

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+library('ggplot2')
+
+data <- read.table(file = 'data.txt', header = TRUE, sep = ',')
+
+plot1 <- ggplot(data, aes(x = region, y = observations)) +
+          stat_summary(fun = mean, geom = 'bar') +
+          scale_y_continuous(expand = c(0,0)) +
+          theme_classic()
+
+plot2 <- ggplot(data, aes(x = region, y = observations, color = region)) +
+          geom_jitter() +
+          scale_y_continuous(expand = c(0,0)) +
+          theme_classic()
+
+#The two plots tell a different story. The barplot loses some information about the data set
+#since it only shows the averages of the data, and nothing about the distribution of the 
+#points within the set. The scatterplot shows that even though these data have similar means,
+#their distribution patterns are different
+
+ggsave('Q2_plot1.jpg', plot = plot1, width = 12, height = 8, dpi = 500)
+ggsave('Q2_plot2.jpg', plot = plot2, width = 12, height = 8, dpi = 500)
+