Apa itu stratified random sampling

organization can branch off the entire population into multiple non-overlapping, homogeneous groups (strata) and randomly choose final members from the various strata for research which reduces cost and improves efficiency. Members in each of these groups should be distinct so that every member of all groups get equal opportunity to be selected using simple probability. This sampling method is also called “random quota sampling”.Age, socioeconomic divisions, nationality, religion, educational achievements and other such classifications fall under stratified random sampling.Let’s consider a situation where a research team is seeking opinions about religion amongst various age groups. Instead of collecting feedback from 326,044,985 U.S citizens, random samples of around 10000 can be selected for research. These 10000 citizens can be divided into strata according to age,i.e, groups of 18-29, 30-39, 40-49, 50-59, and 60 and above. Each stratum will have distinct members and number of members.Recognize the stratification variable or variables and figure out the number of strata to be used. These stratification variables should be in line with the objective of the research. Every additional information decides the stratification variables. For instance, if the objective of research to understand all the subgroups, the variables will be related to the subgroups and all the information regarding these subgroups will impact the variables. Ideally, no more than 4-6 stratification variables and no more than 6 strata should be used in a sample because an increase in stratification variables will increase the chances of some variables canceling out the impact of other variables.Make changes after evaluating the sampling frame on the basis of lack of coverage, over-coverage, or grouping.Figure out the size of each stratum according to your requirement. The numerical distribution amongst all the elements in all the strata will determine the type of sampling to be implemented. It can either be proportional or disproportional stratified sampling.The researcher can then select random elements from each stratum to form the sample. Minimum one element must be chosen from each stratum so that there’s representation from every stratum but if two elements from each stratum are selected, to easily calculate the error margins of the calculation of collected data.Simple Random SamplingTypes of Stratified Random Sampling:In this approach, each stratum sample size is directly proportional to the population size of the entire population of strata. That means each strata = Population size for h Sampling fraction is the primary differentiating factor between the proportionate and disproportionate stratified random sampling. In disproportionate sampling, each stratum will have a different sampling fraction. Stratified Random Sampling Examples:Learn more: ) students of a school having 1000 (N) students were asked questions about their favorite subject. It’s a fact that the students of the 8th grade will have different subject preferences than the students of the 9th grade. For the survey to deliver precise results, the ideal manner is to divide each grade into various strata. Advantages of Stratified Random Sampling:Better accuracy in results in comparison to other probability sampling methods such as cluster sampling, simple random sampling, and systematic sampling or non-probability methods such as convenience sampling. This accuracy will be dependent on the distinction of various strata, i.e., results will be highly accurate if all the strata are extremely different.Due to statistical accuracy of this method, smaller sample sizes can also retrieve highly useful results for a researcher.Learn more: Cluster Sampling vs Stratified SamplingWhen to use Stratified Random Sampling?Stratified random sampling is an extremely productive method of sampling in situations where the researcher intends to focus only on specific strata from the available population data. This way, the desired characteristics of the strata can be found in the survey sample.
  • Researchers rely on this sampling method in cases where they intend to establish a relationship between two or more different strata. If this comparison is conducted using simple random sampling, there is a higher likelihood of the target groups being not equally represented.
  • Samples with a population which are difficult to access or contact, can be easily be involved in the research process using the stratified random sampling technique.
  • The accuracy of statistical results is higher than simple random sampling since the elements of the sample and chosen from relevant strata. The diversification within the strata will be much lesser than the diversification which exists in the target population. Due to the accuracy involved, it is highly probable that the required sample size will be much lesser and that will help researchers in saving time and efforts.
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    Read more about:

    • Consecutive Sampling
    • Quota Sampling
    • Snowball Sampling
    • Quantitative Market Research
    • Qualitative Market Research

    Apa yang dimaksud dengan stratified random sampling?

    Stratified Sampling (Pengambilan Sampel Bertingkat) adalah prosedur pengambilan sampel di mana populasi target dipisahkan menjadi segmen (strata) yang unik dan homogen, dan kemudian sampel acak sederhana dipilih dari setiap segmen (stratum).

    Mengapa menggunakan stratified random sampling?

    Keuntungan yang bisa diperoleh dengan menggunakan stratified random sampling adalah: Mampu memastikan adanya variasi sampel. Mampu memastikan adanya variasi sampel yang serupa. Menurunkan variasi dari secara keseluruhan di dalam suatu populasi.

    Bagaimana cara pengambilan sampel stratified random sampling?

    Langkah - langkah penarikan sampel dalam metode Stratified Random Sampling adalah sebagai berikut : 1) Tentukan dasar stratifikasi (strata), 2) Tempatkan setiap anggota dalam populasi pada strata yang sesuai, 3) Tentukan ukuran sampel (n), 4) Tentukan jumlah sampel yang harus diambil dari setiap strata, 5) Lakukan ...

    Kapan stratified sampling digunakan?

    Stratified sampling, adalah cara penarikan sampel untuk populasi yang memiliki karakteristik heterogen atau karakteristik yang dimiliki populasi bervariasi. homogen, teknik ini juga digunakan bila populasi mempunyai anggota atau unsur yang berstrata (tingkat).