sampling techniques, types of sampling, probability & non probability sampling, Research methodology

DWIVEDI GUIDANCE

6 Dec 202109:49

Summary

TLDRThe video script discusses various sampling techniques used in research, such as simple random sampling, stratified random sampling, systematic sampling, and cluster sampling. It explains the principles behind each method, how they are applied to select samples from a population, and the importance of these techniques in ensuring representative and reliable data for research. The script also touches on non-probability sampling techniques like convenience sampling and snowball sampling, highlighting their advantages and limitations.

Takeaways

📝 The script discusses various sampling techniques used in research, emphasizing the importance of selecting a representative sample from a population.
🔍 It explains the concept of 'Active Setting Technique' where every individual has a chance of being selected in the sample, akin to a lottery system.
🎰 The 'Lottery System' is described as a method where all members of the population have an equal opportunity to be selected, similar to drawing lots.
📚 'Stratified Sampling' is introduced, dividing the population into exclusive groups and then randomly selecting samples from each group to ensure representation.
🔄 'Systematic Sampling' is mentioned, where a systematic pattern is followed to select samples, for example, every tenth individual from a list.
📐 The script touches on 'Cluster Sampling', which involves dividing the population into smaller, manageable groups and then selecting a random sample from these clusters.
🚫 'Non-probability Sampling' is also discussed, where not every element of the population has an equal chance of being selected.
👥 'Convenience Sampling' is highlighted, where samples are collected based on accessibility and convenience rather than randomness.
🔄 'Snowball Sampling' is described, where initial participants are used to refer more participants, growing the sample size through referrals.
📊 The importance of ensuring that the sampling technique used provides a representative view of the population is stressed throughout the script.
📈 The script also covers different scenarios and examples to illustrate how sampling techniques can be applied in various research contexts.

Q & A

What is the concept of 'simply procedure' or 'sampling method' discussed in the script?
-The 'simply procedure' or 'sampling method' refers to the process of selecting a subset of a population, known as a sample, using a sampling camera. It involves techniques to improve the representativeness of the sample and collect data from the population for research purposes.
What are the two main techniques for sampling mentioned in the script?
-The two main techniques mentioned are 'probability sampling' and 'non-probability sampling'. Probability sampling involves every member of the population having a chance of being selected, while non-probability sampling does not guarantee an equal chance for all members.
Can you explain the 'random sampling' technique mentioned in the script?
-Random sampling is a type of probability sampling where every member of the population has an equal chance of being selected. It is compared to a lottery system where all tickets are mixed and a random ticket is drawn to determine the sample.
What is 'stratified sampling' and how does it work?
-Stratified sampling is a method of sampling where the population is divided into exclusive groups, or strata, based on specific characteristics. Random samples are then drawn from each stratum to ensure representation of the various subgroups within the population.
What is the purpose of 'systematic sampling' and how is it conducted?
-Systematic sampling follows a specific system or pattern to select samples. It involves selecting every nth element from a list, ensuring a uniform distribution of the sample throughout the population. For example, if the first sample is chosen randomly, subsequent samples are selected at regular intervals.
What is 'cluster sampling' and how does it differ from other sampling techniques?
-Cluster sampling involves dividing the population into clusters and then randomly selecting some of these clusters for the sample. The difference from other techniques is that the entire cluster is considered as a sample unit, rather than individual elements from the population.
What is meant by 'non-productive sampling technique' in the script?
-A 'non-productive sampling technique' refers to methods where not all elements of the population have an equal chance of being selected for the sample. This could be due to convenience or other factors that bias the selection process.
What is the 'quota sampling' technique mentioned in the script?
-Quota sampling is a non-probability sampling technique where researchers select samples based on certain quotas or criteria. It is similar to stratified sampling but does not require random selection within the strata.
Can you describe the 'snowball sampling' method mentioned in the script?
-Snowball sampling is a method where initial participants in the study recommend others who fit the criteria for the sample. It is useful when the population is hard to access or when the sample size is small, allowing researchers to expand their sample through referrals.
What is 'convenience sampling' and how does it affect the representativeness of a sample?
-Convenience sampling is a non-probability sampling technique where researchers select samples based on their accessibility and ease of collection. While it is practical, it can lead to biased results because it does not ensure a representative sample of the entire population.
What are the ethical considerations when using 'e-sampling techniques' as mentioned in the script?
-Ethical considerations in e-sampling techniques include ensuring the privacy and consent of participants, avoiding bias in the selection process, and ensuring the accuracy and reliability of the data collected through electronic means.

Outlines

00:00

🔍 Sampling Techniques in Research

The paragraph discusses various sampling techniques used in research to collect data from a population. It explains the concept of active setting and non-profit setting techniques, where every individual has an equal chance of being selected. The paragraph also covers different types of sampling such as random sampling, stratified sampling, and systematic sampling. It describes how random sampling works, akin to a lottery system, where every member of the population has an equal opportunity to be selected. Stratified sampling is explained as dividing the population into exclusive groups and then randomly selecting samples from each group. Systematic sampling is described as following a systematic pattern or interval to select samples, ensuring representation from the entire population.

05:02

📊 Non-Random Sampling and Convenience Sampling

This paragraph delves into non-random sampling methods, emphasizing convenience sampling where the researcher selects samples based on accessibility and ease rather than randomness. It also touches on quota sampling, where the researcher divides the population into specific groups and then selects samples to meet certain quotas within those groups. The paragraph further explains snowball sampling, a technique where initial participants help identify additional participants, and mentions the use of chain referral methods to collect data from a wider range of respondents. It concludes with a brief mention of cluster sampling, where the population is divided into clusters, and samples are selected from these clusters to represent the entire population.

Mindmap

Keywords

💡Sampling

Sampling is the process of selecting a subset of individuals from a larger population to represent that population in a study. In the video's context, it's central to the theme as it discusses various techniques of sampling for research purposes. For example, the script mentions 'सैंपलिंग कैमरा' (sampling camera) and 'सैंपल' (samples), which are used to collect data from the population.

💡Random Sampling

Random sampling is a method where every member of the population has an equal chance of being selected. It's a fundamental concept in the video, as it ensures that the sample is representative of the entire population. The script refers to 'सैंपल रेंडम सेंपलिंग' (random sample selection) and compares it to a lottery system, where all tickets are mixed and one is drawn at random.

💡Stratified Sampling

Stratified sampling involves dividing the population into subgroups, or strata, and then taking a random sample from each stratum. This technique is highlighted in the script as 'स्ट्रेटिफाइड सैंपल या फिर स्ट्रेटिफाइड रेंडम सेंपलिंग' (stratified sample or stratified random sampling) and is used to ensure that specific subgroups are adequately represented in the research.

💡Systematic Sampling

Systematic sampling is a method where samples are selected from an ordered population list at regular intervals. The script mentions 'सिस्टेमेटिक सैंपल' (systematic sample) and explains it as selecting every k-th element from a list, which ensures a regular distribution of the sample across the population.

💡Cluster Sampling

Cluster sampling is a technique where the population is divided into clusters, and then a random sample of clusters is selected for the study. The script refers to 'क्लस्टर' (cluster) and explains that the population is divided into areas or groups, from which samples are drawn, which is crucial for understanding the geographic distribution in research.

💡Non-probability Sampling

Non-probability sampling includes various methods where not every member of the population has an equal chance of being selected. The script discusses 'non-productive सैंपलिंग टेक्निक' (non-productive sampling techniques) and contrasts them with probability sampling methods, emphasizing the differences in how samples are selected.

💡Convenience Sampling

Convenience sampling is a non-probability sampling method where samples are chosen based on their ease of access. The script mentions 'कन्वीनियंस सैंपलिंग' (convenience sampling) and gives an example of collecting data from people living in the vicinity, which is a practical approach but may not be as representative.

💡Purposive Sampling

Purposive sampling is a non-probability method where samples are selected based on specific criteria important to the research question. The script refers to 'सैंपल चूज करने के तरीके मेथड' (method of choosing the sample) and discusses how experts or specific groups might be chosen for their relevance to the research.

💡Quota Sampling

Quota sampling is a non-probability technique where the researcher sets a quota for the number of samples in different categories. The script mentions 'कोटा सैंपलिंग' (quota sampling) and explains how it involves dividing the population into categories and selecting a set number of samples from each, ensuring diversity in the sample.

💡Snowball Sampling

Snowball sampling is a method where initial samples are used to refer the researcher to additional samples. The script refers to 'रेफ्रेंस मांगे' (asking for references) and explains how data collection can expand through referrals, which is particularly useful when the population is hard to access.

Highlights

Simple random sampling technique explained, where every member of the population has an equal chance of being selected.

Introduction to stratified random sampling, dividing the population into exclusive groups and then randomly selecting samples from each group.

Systematic sampling method discussed, where samples are selected following a specific system or pattern.

Cluster sampling technique described, where the population is divided into clusters and samples are drawn from these clusters.

Non-probability sampling techniques are introduced, including convenience sampling and its limitations.

Explaining the concept of quota sampling, where researchers select samples based on certain predefined criteria.

The importance of representative sampling in research to ensure the accuracy of the study's findings.

Discussion on the ethical considerations in sampling, ensuring that the sample selection process is fair and unbiased.

Techniques for increasing the response rate in sampling, such as incentives and follow-up contacts.

The role of technology in modern sampling methods, including online surveys and digital data collection.

Comparison between different sampling techniques and choosing the appropriate method based on the research objectives.

The impact of sample size on the reliability and validity of research findings.

Strategies for dealing with non-response in sampling and the potential biases it may introduce.

The process of weighting samples to correct for any imbalances and ensure representativeness.

Exploring the use of stratified random sampling in ensuring diversity in the sample.

The challenges of conducting sampling in diverse and multicultural populations.

Innovative sampling methods being developed to address the evolving needs of researchers.

The future of sampling techniques with the integration of artificial intelligence and machine learning.