This is part two of a completed order #645442. I would like the same writer if they are experts in data analysis. I have two pilot transcripted interviews that I need the Data Analysis indivudally. So that will be two separate Data Analysis write up the 1st on MSW without a clinical license and 2nd MSW with clinical licenses.
By examining the subject’s postgraduate experience, this study will better understand how factors such as the lack of interpersonal relationships, clinical knowledge, and professional expertise affect AAMSWs professional development choices.
The data to be analyzed will be the transcripts of the recorded virtual interviews. The researcher may also refer to the recorded conversations from time to time, but the researcher will generally use the transcripts. Hence, the researcher will require a data analysis method focused on textual analysis.
Listing and Preliminary Grouping (Horizontalization)
For every interview, the researcher will list down relevant information from all the participants. The researcher will identify any relevant information and list it down from the transcripts collected from all the interviews.
Reduction and Elimination
This stage is used to test each expression’s relevance or remark to determine whether it will pass specific requirements: whether the quote/remark is essential to the phenomenon being explored and whether it is possible to label the quote. In this study, the quotes will be tested against their relevance to African Americans’ experiences vis–vis MSW licensure. If any quotes or expressions are found to be vague or cannot be labeled, then they are eligible for elimination.
If any expression that can be labeled and is necessary to understand the phenomena is retained as the invariant constituent. Once the invariant constituents are established, they will then be thematized and clustered. Redundant, overlapping, or repetitive statements are capitalized on and used as essential data. If several subjects said a similar situation affected them, that would indicate that the phenomenon they independently and collectively referred to had a bearing on or influenced their situation.
Clustering and Thematizing the Invariant Constituents
The invariant constituents will then be examined for any latent meanings. Any excerpts and expressions that passed the reduction test will be grouped based on their latent meanings. All the related experiences will be clustered together based on their supposed meanings. Thematized expressions will now be ready for identification of the original data.
Checking Themes Against the Data
The thematized themes will then be checked against the whole transcripts to ensure consistency and that they (the themes) represent the data they are taken from. In this case, for the constituents to be acceptable, they must represent the participants’ experiences as reported by them.
The validity of these themes should be checked based on whether or not they are explicitly expressed in the transcripts, or they are assumed. If they are implied or deduced, these themes should be compatible and consistent with the trends identified from the transcripts. If any of these themes is neither explicit nor compatible, it is rendered irrelevant and may not be considered while making conclusions pertaining to the subjects’ experiences.
Creating Individual Textural Descriptions
In this study, each researcher will analyze each validated theme and derive possible inferences from the information to assign Textural Descriptions. Comments are the basis upon which textural descriptions are derived. A comment like “I hate all this. Imagine having to go through school, spend all those years, sit through all those exams. Has failed their kind.
Creating Individual Structural Descriptions
The experiences of all the participants will be cross-checked and compared from the validated themes. From this, the researcher will be able to make conclusions about the participants’ experiences based on data from each participant. In this case, the researcher identifies dominant themes by comparing all the thematic expressions from the individual participants and uses these comparisons to describe a phenomenon or phenomena. The researcher may combine all the themes to come up with a description of the group.
Creating Composite Structural Descriptions
Once the researcher has generated individual structural descriptions, these will be used to create a composite description. A composite structural description means comparing all the outcomes of each description to formulate a generalized description. In this study, each participant’s experiences will be checked against those of the other participants to try and establish trends, from which conclusions can be made vis–vis the phenomena being explored for example, by inactively comparing the general or predominant feeling among the participants. The researchers may arrive at a finding such as even though many of the interviewed participants felt that their skin color still held a major influence on their experiences as they sought licensure, it was the general feeling that things have changed for the better. Many participants insinuated that they felt the system was improving and that the people of color were now more acceptable and better in society than in the years of yore. However, there is generally an apparent agreement that racial discrimination is far from over, which works against the people of color most if not all of the time.