When should you choose R Line Graphs over Histograms?

a) When you want to show trends over time or the relationship between two continuous variables

b) When displaying the distribution of a single continuous variable

c) When comparing the frequency of discrete categories

d) When illustrating proportions of a whole

Answer:

a) When you want to show trends over time or the relationship between two continuous variables

Explanation:

R line graphs are best suited for showing trends over time or the relationship between two continuous variables. Unlike histograms, which display the distribution of a single continuous variable, line graphs connect data points with a line to illustrate how a variable changes over a continuous range, such as time. This makes them ideal for time series analysis and for visualizing patterns, trends, and relationships between variables.

# Example of a line graph showing a trend over time
years <- c(2016, 2017, 2018, 2019, 2020)
revenue <- c(50000, 55000, 60000, 58000, 62000)
plot(years, revenue, type = "o", col = "blue", xlab = "Year", ylab = "Revenue", main = "Revenue Trend Over Years")

In this example, a line graph is used to display the trend in revenue over five years. The graph effectively shows the upward trend with a slight dip in 2019, making it easy to interpret the data’s overall direction. Line graphs are particularly useful when you need to highlight trends, compare multiple time series, or understand the dynamics of a continuous variable over time.