Sampling and Data Collection in Research Paper

Sampling and data collection is made up of many things and is used in many things. The one main thing is research and in research it helps to obtain information about groups or individuals without being bias. Along with the research, making sure that it is valid and reliable is very important and knowing the ways that research can be done surveys via online or telephone.

The purpose of sampling is that if a researcher decides to research a group, a group can be very large that the information obtained may not be completely accurate.

A researcher can get better information by breaking down the groups into smaller groups and researching them (Monette, 2011). An example of sampling in this case is the large group would be people with PTSD and it can be broken down smaller like researching veterans with PTSD. By breaking the group down for sampling, the data can be obtained more quickly and it is a feasible way of collection.

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There are types of sampling called probability and nonprobability.

Probability sampling is basically randomly picking information, whereas nonprobability sampling is not randomly selecting information. A type of probability sampling is simple random sampling is when the population that is being researched is treated equally as a whole. An example of this is researching a group of college students. A type of nonprobability is snowball sampling which is taking one case of study and that case leads into more cases of study (Monette, 2011). An example of snowball sampling is child abuse because that can lead to more cases not found.

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When it comes to bias the way to avoid it in research and sampling is to make sure that inclusion of all races, cultures, and sexes are provided when picking areas of sampling. On top of sampling there is data collection in research.

Data collection is also known as the scales of measurement in research. The scales of measurement are broken into different levels. The first level is nominal measure which is observations into different categories and an example of this is a favorite hockey player number 11. The second level is ordinal measures which is a category of relationships or ranks. An example of this is like the ranks of the armed forces where each branch has their own rankings. The next level is an interval measure represents numbers and units. An example of this is hockey scores or even the temperature because it can go below zero. The last level is a ratio measure which is the same as the interval measures but it does not go below zero. An example of this is measuring a piece of wood in inches (Monette, 2011).

In the levels of measurement there are types of validity which are construct, face, and criterion. Construct validity represents reality like role playing scenarios as training. Face validity is when something is being testing like children being tested on math and asking parents if the test if working is an example. Criterion validity is showing a relationship between a measurement device and standard like the risk of pedophilia there would be signs of child abuse. It is about the relationship between them (Monette, 2011).

There are types of reliability just like validity which are test-retest, multiple forms, and internal consistency approach. The test-retest is basically is when people take a test and decide to take a retake at a different time. It is the same people just at a different time. Multiple forms are when there are different sets of things like either question to a test or problems to solve. The last one is internal consistency approach which is taking a question and asking it to individuals and comparing it with another individuals answer (Monette, 2011). The reason why it is important to make sure that data collection is valid and reliable is so that there are no errors and that the information that is being collected is not falsely given out to individuals. Along with data collection surveys are used.

Data collection can be done by telephone surveys, online surveys, focus groups, and surveys via websites. The advantages are that the information that is being provided can help a company find its weaknesses and improve them/ The disadvantages are that no one knows who is actually doing the survey because they is not identification being done. The focus group is the one that can have identification but then not much feedback would be given because people not wanting to speak up.

Online surveys would be great because people use the internet a lot to search things. It is a way to get the word out there for surveys and surveys can be much quicker for people online instead of sitting on a phone. It also saves time and sometimes money because some surveys are done in the mail so online saves money.

Sampling and data collection cover lots of area in research with what sampling are and that data collection is the scales of measurement. In research there are different types of validity and reliability that is needed to make sure that the research is done properly and there is no errors when doing it. The last but not least is the different ways to do research like surveys via online and telephone.

Monette, D., Sullivan, T.J., & DeJong, C.R.(2011). Applied Social Research (8th ed.). Retrieved from The University of Phoenix eBook Collection database.

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Sampling and Data Collection in Research Paper. (2016, Apr 24). Retrieved from

Sampling and Data Collection in Research Paper

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