Just like quartiles, percentiles and percentile rank are among the measures of position. Percentiles divide a ranked data (ordered set of data ) into 100 equal parts. 99 percentiles are needed to divide any data set into 100 equal parts.
The data should be ranked in increasing order to compute percentiles.
The kth percentile is denoted by P_{k }where k is an integer from 1 to 99
Just like the first quartile is denoted by Q_{1}, the_{ }first percentile is denoted by P_{1}
Second percentile is denoted by P_{2}
And so forth...
Do you recall the meaning of the first quartile or Q_{1} ?
It means that 25% of the values are less than Q_{1}.
By the same token, first percentile means that 1% of the values are less than P_{1 }or 99% of the values are bigger than P_{1}
In general, the kth percentile , P_{k }, can be defined as a value in a data set such that about k% of the values are smaller than the value of P_{k }and about (100 - k)% of the values are bigger than the value of P_{k}
Percentiles
The value of the kth percentile is P_{k} = the value of the ( kn /100 )th term in a ranked data set
k is the number of the percentile and n is the sample size.
Percentile rank of a value
Percentile rank of x_{i} = (Number of values less than x_{i} / Total number of values in the data set ) × 100
Sep 24, 21 03:39 AM
What is the additive inverse of a complex number? Definition and examples