DISCUSSION ONE: VARIABLES, RESEARCH QUESTIONS 2
Discussion 1: Variables, Research Questions, and Data Coding
Discussion Board One Questions
The ability to understand what variables are, how to create a research topic, and how to
interpret data coding are all very important skills for those who engage in research. Those of us
who are getting close to finishing our doctoral degrees need to thoroughly understand5these three
aspects to complete the last portion of our program successfully. According to Lynch et al.,
(2020), one of the first problems that many graduate research students experience is
understanding5the process of conceiving or framing data and successfully explaining or
anticipating their research findings. A basic understanding of some of the differences,
similarities, and variables will be obtained via5this discussion board, which will focus on
responding5to the question that has been provided.
D1.1. Compare the terms active independent variable and attribute independent variable.
What are the similarities and differences?
When discussing the findings of a research, it is necessary for students to have a solid
understanding of the active and attribute kinds of independent variables that may be classified. A
minimum of one level of an active independent variable is presented to the participants in the
research study. According to Morgan et al. (2019), such examples include changes to the
curriculum and workshops. The researcher is not required to change these active variables;
nevertheless, they are offered to the participants themselves. Attribute independent variables, on
the other hand, are those that cannot be altered and are the core of the investigation (Morgan et
al., 2019). Throughout the course of the study, these variables are representative of aspects of the
persons or their surroundings that do not change.
D1.2. What kind of independent variable (active or attribute) is necessary to infer cause?
DISCUSSION ONE: VARIABLES, RESEARCH QUESTIONS 3
Discussion 1: Variables, Research Questions, and Data Coding
According to Morgan et al. (2019), the statistical procedures that are used in the process
of evaluating research data do not discriminate between an active independent variable and an
attribute independent variable. However, the only procedures that are capable of producing data
that may establish whether the intended variable was responsible for changes or differences in
the dependent variable are those that include an active independent variable.
D1.2.a. Can one always infer cause from this type of independent variable? If so, why? If
not, when can one infer cause and when might causal inferences be more questionable?
An active independent variable alone is not enough to draw cause-and-effect conclusions,
so causality cannot always be inferred from it (Morgan et al., 2019). However, cause can be
deduced when an active independent variable is used in randomized experimental or, to a lesser
extent, quasi-experimental research (Morgan et al., 2019). Causal inferences become
questionable when changes in the dependent variable are based on an attribute independent
variable. For instance, an attribute independent variable can suggest differences or associations
between groups rather than cause changes in dependent variables (Morgan et al., 2019).
D1.3. What is the difference between the independent variable and the dependent variable?
The study approach most importantly depends on the difference between independent and
dependent variables. The element under influence or classification meant to affect another
variable is the independent variable (IV). Study time would be the independent variable (IV) if
we were looking at how test results varied depending on length of time spent studying. Under
their leadership, researchers track changes in test results in response to different study hours. The
dependent variable (DV), on the other hand, is the thing that is being watched in reaction to the
independent variable. The exam results from the same study setting are, therefore, the dependent
variable (DV). The researchers assess exam results and then see how various study strategies
DISCUSSION ONE: VARIABLES, RESEARCH QUESTIONS 4
Discussion 1: Variables, Research Questions, and Data Coding
could affect them. Emphasizing the intricacy of relationships in international business research,
Andersson et al. (2020) address how independent factors might affect dependent variables across
many analytical levels. From this point of view, the complex interactions in which the IV may
have different impacts depending on the degree of investigation or the context are shown.
Morgan et al. (2020) provide a simple and useful method to grasp these ideas in statistical
analysis. Their treatment of independent variables predictors clarifies dependent variables and
the results obtained to test hypotheses. These sources underscore the important goals of IVs and
DVs in study design and analysis. Both are really crucial for the research process; one provides a
theoretical foundation and the other provides sensible statistical direction
D1.4. Compare and contrast associational, difference, and descriptive types of research
questions.
Developing a well organized research question depends mainly on grasping the details of
different research concerns. Morgan et al. (2020) define the many research questions, stressing
their importance throughout the research process. According to Morgan et al. (2020), a thorough
understanding of a phenomenon or variables depends heavily on descriptive research questions.
Those questions provide an overview of the current situation without exploring linkages or
causation. Descriptive inquiries are essentially about precisely depicting variables or scenarios in
painting. One excellent example of a descriptive research topic is the average household income
in a certain community.
Furthermore, looking at the variations between a group or condition is one of the many
research issues (Morgan et al., 2020). The difference inquiry looks at whether groups or
circumstances vary statistically significantly. The difference questions center on group or
DISCUSSION ONE: VARIABLES, RESEARCH QUESTIONS 5
Discussion 1: Variables, Research Questions, and Data Coding
condition comparison. A good example is a difference in the exam scores of students in a
tutoring program compared to those who did not participate.
Lastly, Morgan et al. (2020) state associational research questions examine the
relationship between variables. With associational questions to see whether a change in the
variable is associated with another, they will most often investigate the correlation or causation.
The associational questions look to understand relationships or potential cause-effect links. An
example could be the relationship between the weekly study hours and their academic
performance.
The different research questions will serve other purposes during the research. The
different questions will guide the choice of research design, data collection type, and statistical
analysis that will be used to answer them effectively.
D1.5. Write a research question and a corresponding hypothesis regarding variables
of interest to you but not in the HSB dataset. Is it an associational, difference, or
descriptive question?
Does the level of exercise have an influence on the perceived stress of young students in
college?
There is no association between the level of exercise and the perceived stress that with
students in college.
This question is an associational research question. The questions is looking to examine
the difference between the two variables (level of exercise and the perceived stressed) to see if
any changes in one variable are associated with the change in the other.
D1.6. Using one or more of the following HSB variables, religion, mosaic pattern
test, and visualization score
DISCUSSION ONE: VARIABLES, RESEARCH QUESTIONS 6
Discussion 1: Variables, Research Questions, and Data Coding
D1.6.a. Associational Question: Is there a relationship between mosaic pattern test scores and
visualization scores among students?
D1.6.b. Difference Question: Is there a difference in mosaic pattern test scores between students
of different religions?
D1.6.c. Descriptive Question: What is the average visualization score among students in the
dataset?
References
Andersson, U., Cuervo-Cazurra, A., & Nielsen, B. B. (2020). Explaining Interaction Effects
Within and Across Levels of Analysis. Research Methods in International Business, 331-
349. doi:https://doi.org/10.1007/978-3-030-22113-3_16
DISCUSSION ONE: VARIABLES, RESEARCH QUESTIONS 7
Discussion 1: Variables, Research Questions, and Data Coding
Lynch, J., M Ramjan, L., J Glew, P., & Salamonson, Y. (2020). How to embed a conceptual or
theoretical framework into a dissertation study design. Nurse Researcher, 28(3), 24-29.
doi:https://doi.org/10.7748/nr.2020.e1723
Morgan, G. A., Barrett, K. C., Leech, N. L., & Gloeckner, G. W. (2020). IBM SPSS for
Introductory Statistics: Use and Interpretation (Sixth Edition ed.). New York, NY:
Routledge.
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