1️⃣Simple random which is selecting people completely at random.
🎯Example: Put all 30 classmates' names in a bowl. Mix them, then draw 6 names without looking

2️⃣Systematic - starting with random number and counting with k’th difference like algebraic geometry.
🎯Example: 3, 8, 13, 18, 23, 28, …

3️⃣Stratified which is dividing people into groups and randomly select people from every group.
🎯Example: company needs 12 volunteers for cleaning and they select 9 workers from day shift and 3 workers from night shift.

4️⃣Cluster - randomly chosen one whole group and survey every student from that group.
🎯Example: school should send one class of students to olympics, then choose 1 class among 11 classes, and whole students of that class going to the olympics

Questions? @seva_karimova &

@ismo1l_xoja

1️⃣Quota which is filling group targets without randomness. For example: university needs 10 advisors and ask students who want to be advisor

2️⃣Volunteer - people decide to take part. For example: sending google forms about academic purposes to cifs group, and volunteers will fill the survey

3️⃣Purposive which is selecting people because their knowledge or experience. For example: Exam Cook needs Academic Head and leader chooses a person who got 80+ in last academic year.

4️⃣Haphazard - selecting nearby or accessible people. For example: students need to take an interview from 10 people, and they start from the nearest unknown person

Overall, sampling methods help researchers select a smaller group of people from a larger population in different ways. Understanding the difference between probability and non-probability sampling helps us choose the most suitable method for different research situations.

Questions? @seva_karimova &

@ismo1l_xoja