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Visualizing Data

Histogram are frequently used in data analyses for visualizing the data. Through histogram we can identify the distribution and frequency of the data. Histogram divide the continues variable in groups (x axis) and gives the frequency (y-axis) in each group. The function that histogram use is `hist()`

. Below I will show a set of examples by using `iris`

data set which come with R.

Basic histogram:

hist(iris$Petal.Length)

Adding color and labels in histograms:

hist(iris$Petal.Length, col="blue", xlab="Petal Length", main="Colored histogram")

Adding breaks in histograms to give more information about the distribution:

hist(iris$Petal.Length, breaks=30, col="gray", xlab="Petal Length", main="Colored histogram")

In statistics, histogram is used to evaluate the distribution of the data. In order to show the distribution of the data we first will show density (or probably) instead of frequency, by using function `freq=FALSE`

. Secondly, we will use the function `curve()`

to show normal distribution line.

Here the example:

# add a normal distribution line in histogram hist(iris$Petal.Length, freq=FALSE, col="gray", xlab="Petal Length", main="Colored histogram") curve(dnorm(x, mean=mean(iris$Petal.Length), sd=sd(iris$Petal.Length)), add=TRUE, col="red") #line

Histogram with normal distribution line:

That’s all about histogram in this post, if you have any question leave a comment below.