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Absolute and Relative Frequency in R Programming

Last Updated : 04 May, 2020
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In statistics, frequency or absolute frequency indicates the number of occurrences of a data value or the number of times a data value occurs. These frequencies are often plotted on bar graphs or histograms to compare the data values. For example, to find out the number of kids, adults, and senior citizens in a particular area, to create a poll on some criteria, etc. In R language, frequencies can be depicted as absolute frequency and relative frequency.

Absolute Frequency

Absolute frequency shows the number of times the value is repeated in the data vector. Formula:
 f_1+f_2+f_3+\ldots+f_n=N
where,
 f_i is represented as absolute frequency of each value N represents total number of data values
In R, frequency table of a data vector can be created using table() function. Syntax:
table(x)
where, x is data vector Example: Assume, “M” represents males and “F” represents females in the data vector below.
# Defining vector
x <- c("M", "M", "F", "M", "M", "M", "F", "F", "F", "M")
  
# Absolute frequency table
af <- table(x)
  
# Printing frequency table
print(af)
  
# Check the class
class(af)

                    
Output:
x
F M 
4 6 
[1] "table"

Relative Frequency

Relative frequency is the absolute frequency of that event divided by the total number of events. It represents the proportion of a particular data category present in the data vector. Mathematically,
 n_i=\displaystyle \frac{f_i}{N}
where,
n_i represents the relative frequency of i^{\text{th}} event f_i is represented as absolute frequency of each value N represents total number of data values
In R language, table() function and length of data vector is used together to find relative frequency of data vector. Syntax:
table(x)/length(x)
Example:
# Defining vector
x <- c("M", "M", "F", "M", "M", "M", "F", "F", "F", "M")
  
# Relative frequency table
rf <- table(x)/length(x)
  
# Printing frequency table
print(rf)
  
# Check the class
class(rf)

                    
Output:
x
  F   M 
0.4 0.6
[1] "table"



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