Quantitative research often involves generalising results to a broader population which is only possible if you select a representative sample from a large number of people. Quantitative research helps researchers conduct a broader study which encompasses more people. A broader study requires a broader sample representative of the entire population. And it is only possible in quantitative research, unlike qualitative research, which often utilises a smaller sample size. The usage of probability sampling is frequent in sample selection in quantitative research. This article will tell you the advantages of quantitative research in sample selection.
What is Quantitative Research?
The process of gathering and interpreting numerical data is known as quantitative research. It can be used to identify trends and averages, formulate hypotheses, examine causality, and extrapolate findings to larger populations. It differs from qualitative research, which involves collecting and analysing non-numerical data such as texts, audio, and visual mediums. Quantitative research is a systematic method which gathers quantifiable data and conducts statistical operations on the collected data. Various computational techniques help researchers sort and evaluate the data to generate objective findings.
Researchers use questionnaires, online surveys and polls to gather quantitative data. Different statistical techniques are employed in quantitative methods to conduct research. The descriptive statistical method is used to describe the features of the data set. Whereas inferential statistics help researchers evaluate the findings and draw inferences. The results of quantitative research are generalisable and can help predict future phenomena or future occurrences.
The statistical techniques outlined above are typically used in quantitative research in the social sciences to gather quantitative data from the research participants. Researchers and statisticians use mathematical concepts and frameworks related to the variable under investigation in this research strategy. The frameworks used in quantitative research are thorough, detailed, and frequently even exploratory. This study methodology yields impartial, statistical, and defensible results. Larger samples representative of the total population is used in the structured data collection technique.
What are the advantages of quantitative research in sample selection?
Since the primary aim of quantitative research is to generalise the results of a study’s findings, it seeks larger and authentic study samples by design. Larger samples help researchers derive plausible and credible findings that accurately depict a phenomenon. A sample size representative of the entire population requires appropriate methods and sampling techniques to select an unbiased sample that strengthens the study’s objectives and addresses the research questions. Quantitative research uses the probability sampling technique to select a representative sample.
Probability Sampling in Quantitative research increases sample credibility
Considering the fact that quantitative research aims to extrapolate the study’s findings, probability sampling is the most appropriate strategy for selecting a sizeable representative sample. A study’s findings ought to be generalisable if they can be applied to a larger population that extends beyond the sample from which they were derived. A basic tenet of probability sampling is that to achieve generalizability, each component of the researcher’s sample size has an equal chance of being chosen.
There is no bias originating from the researcher’s beliefs because the sample accurately represents the population. Using the probability sampling technique, researchers can determine the standard error to create credible values for the variable. The overall error can be reduced while saving both time and money by enhancing the probability sampling procedures. Given that there is a systematic procedure to follow, probability sampling methods are substantially easier to carry out. On the other hand, the researcher must carefully consider whether to include a certain feature in the sample when employing non-probability sampling approaches.
Objectivity and Accuracy
Quantitative research helps you design a sample size which leads to objective results since the question template is often close-ended. Quantitative methodology encompasses a few variables which are measured with the help of questionnaires and poll surveys. The survey questions are often close-ended, comprising simple yes/no answers.
What methods can you use for sample selection in quantitative research?
You can use probability sampling in quantitative research to collect a sample from a sizeable population which is representative of the entire population.
Random sampling refers to randomly selecting the sample from a chosen population. It involves assigning each individual a number and then picking it randomly using an automated process from those numbers. The numbers that are chosen are ultimately the sample’s participants. The researchers choose the samples in this sampling method using a random method or a random number generator.
Stratified Random Sampling
The researcher divides a larger population into more coherent segments using stratified random sampling, frequently resulting in groupings that do not overlap but accurately represent the entire population. Before sampling, the researchers divide these groups and randomly select samples from each category. It necessitates grouping or categorising according to sex, age, ethnicity, and other considerations. The subjects are divided into completely unique groups, and then participants are chosen by simple random selection from each category. To ensure that each group member has an equal probability of being selected using basic probability, members of these groups should be varied from one another.
Designing a sample in quantitative research is difficult; it necessitates identifying sampling errors and taking appropriate measures to mitigate or reduce them, which is difficult for novice researchers. However, if you face any difficulty in designing a valid sample size, you can always reach out to experts at Dissertation Help Online and get their assistance in designing a sample.
Random Cluster Sampling
Cluster sampling necessitates segregating the population into smaller units, even though each subgroup should have characteristics in common with the sample size. So instead of selecting random samples from each group, you chose entire portions. Additionally, you can include every individual in each sampled cluster.
Quantitative research is quite helpful in selecting a valid sample size for your research. You can employ probability sampling and its variants for selecting a representative sample. It will help you generalise the results of your research and predict the future behaviour of your study variables.