Research Procedure: Explain The Process of The Research

Research Procedure: Explain the process of the research.
Explain the preliminary preparation:

1. Approval letter from the principal
2. Selection of respondents
3. Construction and validation of the tool
4. Orientation of the respondents
5. Administration of the tool
6. Retrieval of the tool
7. In-Depth Interview and coding
8. Statistical treatment
Research Procedure is a gathering of data after acquiring all the formal permission that the researcher
must acquire from the Graduate School and the locale where the data will be collected, she will then
delve into the gathering of the data needed on the profile, performance, organizational citizenship
behavior, workplace spirituality, organizational cynicism, and work locus of control of the respondents.
For this, the researcher is allotting one (1) month to gather and compile all the data needed.
The researcher will self-administer the questionnaire. Although the research instrument is quantitative
in nature, the researcher deemed it a need to give twenty (20) per respondent per interview. This is
done so that each question can be explained in layman’s terms by the researcher in case some
respondents might have difficulty understanding. This is also done to ensure that all items are answered
correctly. For the level of performance, the researcher will retrieve the performance evaluation results
of the professors after permission has been given. The interpretation of the institutional tool will used to
correlate with the other variables.
For qualitative data, an in depth interview will be done choosing only 5 representative from the
teachers. The representative must fully expressed their willingness to participate and should sign the
informed consent. The in depth interview will be done in the school at about 30 minutes per session.
Data will be coded and interpreted through themes. A 10 minutes documentary video will also be
prepared based on the concept of the problem, findings and conclusion.
Treatment of data is a basically, adjust the data in order to be comprehensive and useful. You probably
is already doing it without naming it.
For example:
Imagine a scenario where a file is provided to ingress data in your application with following columns:
Client ID Name Date of birth Gender Date of marriage
First you have to identify the data consistency, it means, the correctness of the data. What kind of issues
your have to be aware of? BTW - We will not mention here some physical characteristics like language,
file format, delimiters, presence of header, records checksum, etc. that automatically affects the whole
file.
BTW - We will not mention here some physical characteristics like language, file format, delimiters,
presence of header, records checksum, etc. that automatically affects the whole file.
1. Data obligation and uniqueness- is the data obligatory or can be placed in blank? Is the column a
unique key? Is it in fact unique? Was supposed to be ordered between rows?
2. Data type, size and format - is the data placed with correct format (Is client id is numeric and above
0?, are dates in yyyy-mm-dd format and valid?, does name have no numbers or special characters, less
then 100 characters and in upper case?, is gender numeric with one digit only?, and so on)
3. Data limits and domains - is the data, being the right type, containing expected values only? (Is
gender ‘0’ or ‘1’ only, are date of birth and date of marriage previous than today?). Most of the times 2
and 3 are combined in a single step.
4. Inner data relation - is the whole record consistent? (Is date of marriage after date of birth, name is
consistent with gender definition?)
5. Outer data relation - the relation between the received data with already existing data: Is the client
ID a new one or already existing. Is it correct? The outer data must check system domain tables (lookup
tables) too.
These profiling and checks are very simplified of course, but I think you will be able to catch the
approach. So, with the ‘diagnoses obtained from above, we can proceed with the treatment.
The treatment will be one of those bellow:
Reformat the data- for example the name is lower cased - uppercase it.
Correct the data (when possible) - the gender is null but the name is ‘Julia’ - so fill the gender with
Female relative value
Ignore de column - the date of marriage is wrong or before the date of birth - if date of marriage is not
sensitive information and can be null, blank it and accept the rest of the data.
Ignore record - if sensitive information, like name is blank, ignore whole record.
ignore file - if record presents some inconsistency that place it as possibly corrupt - client Id not
number or duplicate, high rate of data type errors, for example, reject the whole file to be evaluated or
resent.
Treatment of data is the term “statistical treatment” is a catch-all term which means to apply any
statistical method to your data. A way to gain a deeper understanding of an event, organization or
culture. Depending on what type of phenomenon you are studying, QR can give you a broad
understanding of events, data about human groups, and broad patterns behind events and people.
While traditional lab-based research looks for a specific “something” in the testing environment,
qualitative research allows the meaning, themes, or data to emerge from the study.
Definition of terms a definition list is a list of terms and corresponding definitions. The definition text is
typically indented with respect to the term. An alternative format places the term left aligned in a wide
margin and the definition on one or more lines to the right of the term.

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Research Procedure: Explain the process of the research.

Explain the preliminary preparation:

Client ID Name Date of birth Gender Date of marriage

The treatment will be one of those bellow:

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