15 คิว
6th
11 คิว
9th - 12th
32 คิว
12th
15 คิว
6th
30 คิว
6th - 8th
12 คิว
Uni
58 คิว
11th
17 คิว
6th - Uni
10 คิว
6th
24 คิว
6th
11 คิว
8th
20 คิว
6th - Uni
20 คิว
6th - Uni
10 คิว
9th - 12th
10 คิว
6th - Uni
20 คิว
6th - Uni
6 คิว
10th
19 คิว
8th
35 คิว
7th
20 คิว
11th - 12th
15 คิว
6th
21 คิว
7th
16 คิว
9th
20 คิว
7th
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Explore printable Quartiles worksheets
Quartiles worksheets available through Wayground (formerly Quizizz) provide comprehensive practice in understanding and calculating the statistical measures that divide datasets into four equal parts. These educational resources strengthen students' ability to find the first quartile (Q1), median (Q2), and third quartile (Q3) while developing proficiency in interpreting interquartile ranges and identifying outliers in data distributions. The collection includes free printables with detailed answer keys, practice problems ranging from basic quartile identification to complex box plot construction, and pdf formats that accommodate various learning environments. Students work through exercises involving both small and large datasets, learning to organize data, determine quartile positions using different methods, and apply quartile concepts to real-world statistical scenarios.
Wayground (formerly Quizizz) supports mathematics educators with an extensive collection of teacher-created quartiles worksheets drawn from millions of educational resources that can be easily searched, filtered, and customized to meet diverse classroom needs. The platform's robust differentiation tools allow teachers to modify worksheet difficulty levels, adjust problem complexity, and select specific quartile calculation methods to match student readiness levels and curriculum standards. These flexible resources are available in both printable and digital formats, including downloadable pdf versions, enabling seamless integration into lesson planning, targeted remediation for students struggling with statistical concepts, and enrichment opportunities for advanced learners ready to explore quartiles in more sophisticated data analysis contexts.
