Analysis on Univariate 2022

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Univariate Analysis
Name:
Institution

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1. Bar plots
Year<-c(1890, 1895, 1900, 1905, 1910, 1915, 1920, 1925, 1930, 1935, 1940)
Journal.volume<-c(1,5,5,6,9,12,13,15,21,21,27)
boring<-data.frame(Year,Journal.volume)
barplot(Journal.volume, Year, names.arg = Year,col="steelblue",ylab="Journal
Volume",xlab = "Years")
2. Scatter Plot
X<-c(1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 6, 7)
Y<-c(1, 2, 3, 3, 4, 4, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7)
plot(X,Y, ylab = "Variable Y",xlab = "Variable X")
abline(lm(Y~X))
lines(lowess(X,Y),col="red")

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As evident, the lowess curve (red) tends to fit the in the plot better than the trend line
since it creates a smoothline through the plot, which aids in exhibiting the relationship
between the variables
3. Google Ngram Viewer
a)
b) The graph above shows that behavior, cognitive, and neuroscience all start at
point 0 whereas psychological science has higher starting point. Moreover, it is
evident that psychological science does not have change rather it is stagnant
across the years. On the other side, both neuroscience and cognitive science
exhibit growth from 1975.
c) To avoid drawing over broadly conclusions to a chart it is recommendable to label
lines individually and highlight the most important characteristics of the chart. For