The Empirical Data Collection Process Essay

When conducting research data is gathered from a sample. The data can prove or disprove the hypothesis. When reviewing the data, a person can become bias and only use the data that they feel is beneficial to their study. Rubin and Babbie (2014) write about the two types of sampling bias: Conscious and Unconscious. The authors state “When we speak of bias in connection with sampling, this simply means those selected are not typical or representative of the larger populations from which they have been chosen” (Rubin & Babbie, 2014).

added to the limitations of the method. It could be argued that random sampling would provide a

The researchers used purposive sample but did not give any explanation as to why this choice sampling was made. It is essential to describe the sampling process in a research where this facilitates the reader to distinguish any bias in the whole sampling process. In studies using participants, the process of how to select, access, inform and retain research participants requires considerable thought. Sampling is a key issue, because it is

Luker describes sampling through canonical social science research as a “systemic random probability sample”, with the goal of producing results that can then be apply and a general way. For example, with a research question that focuses on voting in a election, A canonical social science research question may trying to determine how many voters are expected to vote a certain way in a election. By using randomly sampling a certain number of voters could be surveyed the result can provide a general description of the voting trend of an entire populations with similar characteristic as the sample group. While I agree with Luker that sampling is important to both canonical qualitative and qualitative social science research, in the case of qualitative research, the word has different meaning.

According to Acharya, Prakash, Saxena, and Nigam (2013), sampling designs are classified into two categories: probability sample and non-probability sample. Probability sampling aids in the generalizability of the results because individuals in the population have an equal chance of being selected to participate in the study (Acharya et al., 2013). With the non-probability sampling method, every individual does not have the same chances of being included (Frankfort-Nachmias, & Nachmias,

Probability sampling, also known as random sampling, requires that every member of the study population have an equal opportunity to be chosen as a study subject. For each member of the population to have an equal opportunity to be chosen, the sampling method must select members randomly. Probability sampling allows every facet of the study population to be represented without researcher bias. Four common sampling designs have been developed for selection of a random sample: simple random sampling, stratified random sampling, cluster sampling, and systematic sampling (Burns & Grove,

Thus, this method gives a researcher an in-depth understanding of the participants’ experiences using qualitative inquiry to determine the why, when, where, what, and how of the study.

Based upon information provided this study was appropriate conducted as a purposeful sampling but, this study

In this essay, I will appraise the sampling methods used in the following two case studies:

179). This is an important statement as it means the researcher needs to start thinking about how they will analyze their data before they even collect it. In order to properly analyze the data, the researcher should transcribe each interview and then compare it to their observations and journal (Badenhorst, 2008). When analyzing the data the researcher must keep in mind the research questions, and create themes through the data that relate to the research question. First, the researcher will analyze each session together, coming up with keynotes and themes from the observations, interviews, and journals (Anderson & Austin, 2012). Once that is analyzed, each piece from each session will then be compared with each other. For example did participants enjoy the program in session 1 but not by session 5? Why did this happen? Was the program too repetitive? Was it the same thing over and over? Was there a different instructor? After the analysis is done the researcher must put the data into a legible discussion

Prior to this course I thought I could look at current research and appraise a study; however, after this course I determined my knowledge about research studies was limited. Now when I look at the sampling methods and how the data was analyzed I can review it with a new lens. This is especially evident with how samples are determined. Establishing how a sample will be taken is of utmost importance and according to Polit and Beck (2017) validity of a study is directly impacted by how the sample is obtained and how it can be generalized to the overall population. Many factors can cause a sample to not be representative or result in bias through convenience sampling. When I look at a study now I look at

To ensure the results of the research are ethical and valid a proper sample design is necessary. A sample design consists of methods, sample frame, and sample size.

This is because it is an on-going observation and interview that will lead to interpretive analysis through themes, patterns and narrative synthesis among others. The method will lead to inductive findings through creative and critical reflection of the researcher. The situation therefore, requires an ongoing process so that the researcher may understand the situation through the changes that he or she observes in the course of time. This method is a journey in which experiences are built on the previous ones.

Sampling strategy is a focus on a smaller group to determine the conclusions of the larger population (Cooper & Schindler, 2014, p. 338). In this instance, the McMahon Group employed both focus groups and mail surveys as strategies to gather information and the dual approach produced relevant and valuable data for researchers.

The behavior was observed from a large sample of people. This included twenty people shopping alone and twenty people shopping in a group, for a total of forty subjects, each ranging in ages from approximately 19 to 40 years old. The subjects were observed from the time they entered the store until the time they left. The reasoning behind this was to see the buying behavior differences for the whole experience and figure out which areas of the store could be improved in order to appeal to groups of people shopping. The behaviors observed included the amount of time spent inside the store, the amount of money spent, the interactions with associates, and the areas of the stores that were navigated.