Teknik Sampling
Ringkasan
TLDRThe video provides an overview of sampling techniques in quantitative research, emphasizing the importance of selecting representative samples from a population. It explains the concepts of target population, source population, and the distinction between probability and non-probability sampling methods. Various probability sampling techniques are detailed, including simple random sampling, stratified sampling, cluster sampling, and multistage sampling. An example is given to illustrate how these techniques can be applied in research, specifically in studying obesity prevalence among middle school students.
Takeaways
- 📊 Understanding sampling is crucial for research validity.
- 🎯 Target population is the group you want to study.
- 🔍 Probability sampling gives every member a chance to be selected.
- 📋 Non-probability sampling does not guarantee equal selection chances.
- 🎲 Simple random sampling ensures equal opportunity for all members.
- 📈 Stratified sampling improves representation by grouping populations.
- 🏫 Cluster sampling involves selecting entire groups for study.
- 🔄 Multistage sampling combines different sampling methods.
- 👩🎓 Example: Studying obesity in middle school students.
- 📅 Stratification ensures diverse representation in samples.
Garis waktu
- 00:00:00 - 00:08:43
This video introduces the concept of sampling in quantitative research, emphasizing the importance of selecting representative samples from a defined population. The target population consists of individuals with specific characteristics, while the source population refers to a segment of the target population that is accessible to researchers. Different sampling methods can be categorized into probability sampling and non-probability sampling, the former allowing all population members an equal chance of selection. Methods of probability sampling include simple random sampling, stratified sampling, clustered sampling, and multistage sampling. The video explains these techniques in detail, particularly focusing on how to ensure representative samples, including the use of random selection and stratification to achieve a robust data set. Towards the end, a practical example involving the study of obesity prevalence among middle school students in a city is discussed, illustrating the application of the cluster and stratified sampling techniques to achieve a credible research outcome.
Peta Pikiran
Video Tanya Jawab
What is the main focus of the video?
The video focuses on sampling techniques in quantitative research.
What are the two main types of sampling techniques discussed?
The two main types are probability sampling and non-probability sampling.
What is simple random sampling?
Simple random sampling is a method where each member of the population has an equal chance of being selected.
What is stratified sampling?
Stratified sampling involves dividing the population into subgroups and randomly selecting samples from each subgroup.
What is cluster sampling?
Cluster sampling groups the population into clusters and then randomly selects entire clusters for the study.
What is multistage sampling?
Multistage sampling combines several sampling techniques, such as selecting clusters and then sampling within those clusters.
What is the example used in the video?
The example discusses studying obesity prevalence among middle school students in a city.
How is stratification used in the example?
Stratification is used to ensure representation from both public and private middle schools.
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- sampling
- quantitative research
- probability sampling
- non-probability sampling
- simple random sampling
- stratified sampling
- cluster sampling
- multistage sampling
- obesity prevalence
- middle school