One thing that distinguishes quantitative research works from qualitative research works is the use of statistical data. This is because as noted by Hunter and Leahey (2008), in quantitative research, researchers put a lot of emphasis on the use of statistical and mathematical data. …
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In a quantitative research, the sample refers to a group of people among the population with who the researcher has direct interaction or encounter with as part of the data collection process. The population can therefore be said to be a very large set made up of several people but the sample a subset within the larger set from who data is collected. Reading through reading through the work of Gall, Gall and Borg, one gets the understanding that having a sample is important for several reasons. In the first place, having a sample is very important to ensure that the researcher can have a group of people who can be handled well in relation to the time available for the study. What this means is that when there are so many people to deal with at a time, it may be difficult to perform an in-depth data collection. What is more, sample can be used to ensure that the researcher uses only people with the right form of information that the researcher seeks for the study.
After the sample has been developed, a researcher may go ahead to collect data from the respondents or participants within the sample. Performing data collection can be very difficult for researchers and can even impact on the outcome of the study if the right data collection procedure is not selected. With this, Gall, Gall and Borg (2008) noted that there are several data collection procedures which are often defined under the research strategy that the researcher uses. For most quantitative research, the use of survey is used as the most preferred data collection procedure.
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