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Student Name SANDEEP KAUR
Student Id A00164627
Course name BUSINESS MANAGMENT
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answer all questions below,
1. What is your stand on anti-racism and our society?
2. As a society, can we talk about issues like feminism and racism openly?
3. Feminist practice-in theory, has posed new questions regarding the role of culture and roles in society, what are these?
4. What are the issues related to post modernism?
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| Research Study Document |
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Student Name: SANDEEP KAUR
Student ID: A00164627
Course Name: BUSINESS MANAGEMENT
Submitted To: PUSPDEEP SINGH
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Page 1 of 5
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When conducting research studies, one of the crucial considerations is selecting an appropriate sampling method. Sampling methods can broadly be classified into two categories: probability sampling and non-probability sampling. This essay aims to discuss the differences between these two sampling approaches, provide examples of probability sampling techniques, compare simple random sampling and stratified random sampling, and analyze the advantages and disadvantages of using non-probability sampling methods in research.
Probability sampling involves selecting a sample from a population using a random process that ensures every individual in the population has an equal chance of being chosen. It allows researchers to make statistical inferences and estimate the characteristics of the population accurately. In contrast, non-probability sampling does not involve random selection, and the researcher relies on their judgment or convenience to select participants. This approach may result in a biased sample, limiting the generalizability of the findings.
There are several common examples of probability sampling techniques used in research studies. One such technique is simple random sampling, where each individual in the population has an equal probability of being selected. It is often used when the population is relatively small and homogeneous. Another example is stratified random sampling, which involves dividing the population into distinct strata and then randomly selecting individuals from each stratum. This technique ensures representation from different subgroups within the population and is useful when the population is heterogeneous.
In terms of sample selection, simple random sampling differs from stratified random sampling. Simple random sampling selects participants entirely at random, without considering any specific characteristics. On the other hand, stratified random sampling divides the population into subgroups based on certain characteristics (e.g., age, gender, socioeconomic status) and then selects participants randomly from each subgroup. This allows for a more representative sample that captures the diversity present in the population.
Non-probability sampling methods have their own set of advantages and disadvantages. One advantage is that they are often quicker and more cost-effective than probability sampling methods. Non-probability sampling can be useful when it is challenging to access the entire population or when the research question is exploratory in nature. However, non-probability sampling methods also have limitations. Since participants are not selected randomly, the sample may not accurately represent the population, leading to biased results. This restricts the generalizability of the findings to the larger population.
In conclusion, probability sampling and non-probability sampling methods differ in their approach to participant selection and the level of generalizability they offer. Probability sampling ensures equal chances of selection and allows for statistical inference, while non-probability sampling methods rely on researcher judgment and convenience. While non-probability sampling can be advantageous in certain research scenarios, it is important to acknowledge the potential biases and limitations associated with this approach. Researchers should carefully consider the research objectives, population characteristics, and available resources when choosing an appropriate sampling method.
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Keywords: probability sampling, non-probability sampling, simple random sampling, stratified random sampling, sample selection, advantages, disadvantages, representativeness, bias.
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Table of Contents:
1. Introduction
2. Probability Sampling
2.1 Simple Random Sampling
2.2 Stratified Random Sampling
3. Non-Probability Sampling
4. Comparison of Simple Random Sampling and Stratified Random Sampling
5. Advantages and Disadvantages of Non-Probability Sampling
6. Representativeness in Non-Probability Sampling
7. Conclusion
8. References
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