Partition Values: Quartiles, Deciles, and Percentiles for Individual, Discrete, and Continuous Series | Measures of Dispersion | Descriptive Statistics | Statistics and Data Analysis
PARTITION VALUES
The Partition Values in Statistics are important measures to study the variation in the data more deeply. Quartiles, Deciles, and Percentiles are known as Partition Values. Partition Values divide a large amount of data into equal parts. The objective of using the partition values is to divide the data into equal parts or equal sections so that we could identify the variation of the data in different parts and take corrective action to reduce the variation in that part of the data where the variation is high.
QUARTILES
Quartiles divide a data series into four equal parts. For any data series, there are three Quartiles: Q1, Q2, and Q3. Q1 is the first or lower Quartile; 25% of data values lie below it. Q2 is the second Quartile also called the Median. 25% of data values lie between Q1 and Q2 and hence 50% of data values lie below Q2. 25% of data values lie between Q2 and Q3 and hence 75% of data values lie below Q3, the third quartile. And the last part of 25% of data values lies above the Q3.
======25%======Q1======25%======Q2======25%======Q3======25%======
DECILES
Deciles divide a data series into 10 equal parts. For any data series, there are 9 Deciles: D1, D2, D3, D4, D5, D6, D7, D8, and D9. Each part or segment of the data has 10% data values
PERCENTILES
Percentiles divide a data series into 100 equal parts. For any data series, there are 100 Percentiles: P1, P2, P3,………P40, P41,........ P70, P71,…………P98, and P99.
CHAPTERS
0:00 Introduction
1:44 Partition Values
4:08 Quartiles for an Individual and Discrete Series
4:45 Deciles for an Individual and Discrete Series
5:20 Percentiles for an Individual and Discrete Series
6:18 Example: Individual Data Series
7:52 Example: Discrete Data Series
10:00 Quartiles for Continuous Series
12:50 Deciles for Continuous Series
15:07 Percentiles for Continuous Series
17:24 Recap
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