Operations Management homework help

Please make sure that it is your own work and not copy and paste off of someone work because my professor will know. This is a DBA course and needs to be done on this level. Please read the study guide. Please use the APA 7th format edition. Please watch out foe spelling and grammar errors.

Book Reference: Gliner, J. A., Morgan, G. A., Leech, N. L. (2017). Research methods in applied settings: An integrated approach to design and analysis (3rd ed.). Routledge. https://online.vitalsource.com/#/books/9781317526896

Considering the five quantitative approaches described in Chapter 7 in the textbook, pick two approaches, and explain them

RCH 8301, Quantitative Research Methods 1
Course Learning Outcomes for Unit II
Upon completion of this unit, students should be able to:
1. Differentiate between quantitative, qualitative, and mixed methods research design methods.
1.1 Analyze descriptive, comparative, and associational research approaches.
2. Distinguish between experimental, quasi-experimental, and nonexperimental research designs.
2.1 Discuss the similarities and differences between experimental, quasi-experimental, and
nonexperimental research methods.
Course/Unit
Learning Outcomes
Learning Activity
1.1
Unit Lesson
Chapter 4, pp. 56–66
Chapter 5, pp. 69–85
Chapter 6, pp. 89–102
Chapter 7, pp. 106–117
Chapter 8, pp. 120–130
Unit II Essay
2.1 Unit II Essay
Required Unit Resources
Chapter 4: Research Approaches, pp. 56–66
Chapter 5: Randomized Experimental and Quasi-Experimental Designs, pp. 69–85
Chapter 6: Single-Subject Designs, pp. 89–102
Chapter 7: Nonexperimental Approaches/Designs, pp. 106–117
Chapter 8: Internal Validity, pp. 120–130
Unit Lesson
Research Approaches
In this unit, we will learn that research is conducted to analyze a problem and that research is mainly
deployed to clarify a generalized assumption. Research tries to explain the problem and tries to identify its
solution. Theories and observations are the pillars of research, and they strengthen each other. From an
observation, a theory can be inducted, and from a theory, observation can be deduced. Research is done to
unravel things that were hidden earlier, and research methods are used to shape how research is created,
how it is conducted, and how those findings can be theorized. Research methods has become a field of
academic inquiry, and, over the years, it has created a body of knowledge and approaches to constructing,
conducting, and theorizing research.
The research approaches can be broadly separated into the 1) randomized experimental approach and the 2)
quasi-experimental approach.
UNIT II STUDY GUIDE
Quantitative Research Approaches,
Questions, and Designs
RCH 8301, Quantitative Research Methods 2
UNIT x STUDY GUIDE
Title
Randomized Experimental Approach
The randomized experimental approach is the most rigorous form of experimental research. It prevents
selection bias and ensures against accidental bias. Randomized experimental research is considered the gold
standard against which all other types of research are compared. Experimental research is done either to
accept or reject a hypothesis, and these experiments are conducted in order to answer a generalized
assumption and to check for its validity.
The aim of this kind of research is to find the cause-and-effect relationship, and it is primarily carried out to
understand the causal relationship. Researchers manipulate the variable to a control group and will note the
changes (if any happens). They note such changes in order:
1. to identify the causal relationship (the effect happens only when the cause happens);
2. to verify the consistency of the cause and effect (whenever the cause changes, it also changes the
effect); and
3. to quantify the relationship between the change and the effect.
Before starting an experiment, the researcher should visualize what he or she needs. The researcher must
note the observations that were deduced from the earlier theories. The gaps must be identified in the
research and addressed. If the problem is properly designed, it is halfway to solution.
Two sets of the people who are selected from similar backgrounds are formed groups. The group is made in
such a way that one group is equivalent to another. This experiment happens in a controlled environment. In
the two groups, there is a control group in which the settings of the groups are manipulated, and another
group is denied what the first group gets. Now the difference in them is noted.
In this stage, the obtained data is analyzed, and a conclusion is drawn from it. The conclusion is studied with
the observation of the similarities and the deviations—both of which are noted. The data here is known as the
raw data. The important thing about research is its transparency and consistency. The data of the research
should be made public so that anyone interested can cross-check and validate the findings.
Research Designs
In the previous unit, there was an initial explanation of variables.
We learned that there are two kinds of variables: independent
variables and dependent variables. Independent variables can
be explained as the cause, while dependent variables are the
effect of that cause. When there is manipulation in the
independent variable, there is a change in the dependent
variable.
The independent variable can be further divided into an active independent variable or an attribute
independent variable (Gliner et al., 2017). A variable that can be manipulated by the researcher is known as
the active independent variable. In a controlled experiment, this variable can be manipulated. For example, in
a dieting experiment, if the researcher changes the dieting regimen, then that variable is known as the active
independent variable.
A variable that cannot be manipulated by the researcher is known as the attribute independent variable. Even
in a controlled experiment, certain characteristics are beyond the researcher’s ability to manipulate, and such
characteristics describe an attribute independent variable. For example, the participant’s age, race, and
mental rigor fall beyond the purview of the researcher’s manipulation, and such characteristics describe an
attribute independent variable.
As human nature can be frail, there is always an inherent bias in selection. In order to reduce this bias, the
randomization method is used to select the sampling, and human intervention in selecting the participant
should be kept to a minimum. Randomization enhances the conclusion of the experiment overall.
(Plantfelicity, n.d.)
RCH 8301, Quantitative Research Methods 3
UNIT x STUDY GUIDE
Title
Quasi-Experimental Design
There are many areas where the randomized experimental designs cannot be used. To study such
conditions, quasi-experiments are considered a suitable alternate. In the researcher’s world, this model is
unscientific and unreliable as it does not carry the same rigorous standards of the experimental design.
Nevertheless, it can be used to measure huge sizes such as cross-cultural behaviors or public policy
effectiveness in similar communities.
In this design, the researchers can only observe the causal variable but are not able to manipulate it. These
types of research approaches are more realistic than the experimental designs as they reflect the real world.
Reactions of the test subjects are more realistic, and the outcomes can be closer to the answers. These
experiments reinforce the experiments in a controlled environment and can be used to increase its reliability.
However, they are more prone to human error. The bias is much more prominent than in the controlled
experiments (Price et al., 2015).
Nonequivalent Group Design
Nonequivalent group research design is one of the most frequently used in research where the researcher
does not assign these types of groups. When participants are not selected and controlled, the groups tend to
be more dissimilar. Nonequivalent groups can be defined as the groups where the participants are selected
nonrandomly and post-intervention studies are conducted. We try to select groups that are as similar as
possible so that we can fairly compare the treated one with the comparison one (e.g., average educational
qualifications across various cultures, effectiveness of public policies across similar income countries).
In nonequivalent group design, only one group is exposed to the treatment, and the other is not. When a new
intervention is made in an ongoing project, this method can be used to gauge the effectiveness of the
program. For example, a posttest intervention can be made to assess a new teaching method in a school. Its
outcome can be noted. If similar groups are selected for the experiment, it will increase the reliability of the
experiment and will reduce the confounding variables.
To increase the reliability and credibility of the posttest design, pretest and posttest intervention can be
introduced. A treatment group is given pretest and posttest intervention before and after the introduction of
the changes. The nontreatment group where no such change applies also can be given this intervention to
measure how effective the change is. For example, you could introduce a nutritional intervention scheme in a
school. The pretest and posttest design can bring out how the nutrition of the child improves the learning
outcomes of the child.
The time series research design takes measurements over a series of time. Data is gathered periodically in a
timely order, and the data consistency is checked. Time series design is relevant across various research and
observational studies, and the long-term deviation, impact, and change of a phenomenon can be measured.
Time series is a repeated periodical measurement that is taken across equally spaced time intervals. For
example, the level of rain across a region through various time periods can strengthen the climatic models.
The public policy’s health can be measured by analyzing its effectiveness. The data gathered when the policy
was introduced (i.e., how the landscape has changed in the midcourse and its lasting impact) can be
measured through the time series model.
Nonexperimental Research Design
Nonexperimental research is normally descriptive or correlational since variables cannot be manipulated, and
participants cannot be assigned randomly; therefore, no causal nature can be determined. The nature of the
research question determines whether the researcher chooses between an experimental and
nonexperimental research design. If the research question involves a causal relationship and an independent
variable that can be manipulated, the experimental approach is typically preferred. However, a
nonexperimental research design is preferred when there is a single variable being studied, when there is not
an active independent variable, or when there is a non-causal statistical relationship between variables.
Although nonexperimental research can be both quantitative and qualitative, our focus will be on the three
quantitative nonexperimental research approaches: descriptive, associational, and comparative. Many
RCH 8301, Quantitative Research Methods 4
UNIT x STUDY GUIDE
Title
research studies contain more than one hypothesis, so many use a combination of research approaches to
construct the hypotheses.
Internal validity
One factor in determining the quality of a research study is
its internal validity. Validity is a tool to measure whether the
intention of the research matches the outcome of the
research, and it measures how well an experiment is done. It
shows the confidence that can be placed in the cause-andeffect relationship in the research study. Internal validity
shows us how well a study is organized and executed to
prevent errors and bias. The internal validity’s scope is within
the research only and focuses on these issues:
 How well was the research done?
 Does it have confounding variables?
Internal validity and confounding variables share an
inversely proportional relationship. When the confounding
variables increasingly affect the outcome, the internal validity will be less. The higher the internal validity, the
higher the credibility of the research will be (Trochim, 2006).
There are a number of potential threats to internal validity. Threats, such as maturation (i.e., when the
participants in the study change over time) and history (i.e., when an event occurs beyond the researcher’s
control), affect the outcome of a study. Another influencing factor is testing, which is when participants do
better on the posttest than on the pretest due to the experience gained. Instrument occurs when there is
inconsistency between the last interview and the first one (Gliner et al., 2017). Therefore, it is important to
have a well-designed research study with high internal validity.
References
Gliner, J. A., Morgan, G. A., & Leech, N. L. (2017). Research methods in applied settings: An integrated
approach to design and analysis (3rd ed.). Routledge.
Hafakot. (n.d.). Data validity concept (ID 88877337) [Illustration]. Dreamstime.
https://www.dreamstime.com/stock-illustration-data-validity-concept-d-illustration-title-businessdocument-image88877337
Plantfelicity. (n.d.). Newton cradle, cause and effect concept, blue infinity Newton`s cradle 3d illustration
banner (ID 110665870) [Illustration]. Dreamstime. https://www.dreamstime.com/close-up-newton-scradle-newton-cradle-cause-effect-concept-blue-infinity-newton-s-cradle-d-illustration-bannerimage110665870
Price, P. C., Jhangiani, R., & Chiang, I. A. (2015). Research methods in psychology.

Quasi-Experimental Research


Trochim, W. M. (2006). Internal validity. Conjoint.ly. http://www.socialresearchmethods.net/kb/intval.php
Learning Activities (Nongraded)
Nongraded Learning Activities are provided to aid students in their course of study. You do not have to submit
them. If you have questions, contact your instructor for further guidance and information.
Review the “Interpretation Questions” and “Application Problems” at the end of Chapters 4, 5, 6, 7, and 8.
(Hafakot, n.d.)RCH 8301, Quantitative Research Methods 1
Course Learning Outcomes for Unit II
Upon completion of this unit, students should be able to:
1. Differentiate between quantitative, qualitative, and mixed methods research design methods.
1.1 Analyze descriptive, comparative, and associational research approaches.
2. Distinguish between experimental, quasi-experimental, and nonexperimental research designs.
2.1 Discuss the similarities and differences between experimental, quasi-experimental, and
nonexperimental research methods.
Course/Unit
Learning Outcomes
Learning Activity
1.1
Unit Lesson
Chapter 4, pp. 56–66
Chapter 5, pp. 69–85
Chapter 6, pp. 89–102
Chapter 7, pp. 106–117
Chapter 8, pp. 120–130
Unit II Essay
2.1 Unit II Essay
Required Unit Resources
Chapter 4: Research Approaches, pp. 56–66
Chapter 5: Randomized Experimental and Quasi-Experimental Designs, pp. 69–85
Chapter 6: Single-Subject Designs, pp. 89–102
Chapter 7: Nonexperimental Approaches/Designs, pp. 106–117
Chapter 8: Internal Validity, pp. 120–130
Unit Lesson
Research Approaches
In this unit, we will learn that research is conducted to analyze a problem and that research is mainly
deployed to clarify a generalized assumption. Research tries to explain the problem and tries to identify its
solution. Theories and observations are the pillars of research, and they strengthen each other. From an
observation, a theory can be inducted, and from a theory, observation can be deduced. Research is done to
unravel things that were hidden earlier, and research methods are used to shape how research is created,
how it is conducted, and how those findings can be theorized. Research methods has become a field of
academic inquiry, and, over the years, it has created a body of knowledge and approaches to constructing,
conducting, and theorizing research.
The research approaches can be broadly separated into the 1) randomized experimental approach and the 2)
quasi-experimental approach.
UNIT II STUDY GUIDE
Quantitative Research Approaches,
Questions, and Designs
RCH 8301, Quantitative Research Methods 2
UNIT x STUDY GUIDE
Title
Randomized Experimental Approach
The randomized experimental approach is the most rigorous form of experimental research. It prevents
selection bias and ensures against accidental bias. Randomized experimental research is considered the gold
standard against which all other types of research are compared. Experimental research is done either to
accept or reject a hypothesis, and these experiments are conducted in order to answer a generalized
assumption and to check for its validity.
The aim of this kind of research is to find the cause-and-effect relationship, and it is primarily carried out to
understand the causal relationship. Researchers manipulate the variable to a control group and will note the
changes (if any happens). They note such changes in order:
1. to identify the causal relationship (the effect happens only when the cause happens);
2. to verify the consistency of the cause and effect (whenever the cause changes, it also changes the
effect); and
3. to quantify the relationship between the change and the effect.
Before starting an experiment, the researcher should visualize what he or she needs. The researcher must
note the observations that were deduced from the earlier theories. The gaps must be identified in the
research and addressed. If the problem is properly designed, it is halfway to solution.
Two sets of the people who are selected from similar backgrounds are formed groups. The group is made in
such a way that one group is equivalent to another. This experiment happens in a controlled environment. In
the two groups, there is a control group in which the settings of the groups are manipulated, and another
group is denied what the first group gets. Now the difference in them is noted.
In this stage, the obtained data is analyzed, and a conclusion is drawn from it. The conclusion is studied with
the observation of the similarities and the deviations—both of which are noted. The data here is known as the
raw data. The important thing about research is its transparency and consistency. The data of the research
should be made public so that anyone interested can cross-check and validate the findings.
Research Designs
In the previous unit, there was an initial explanation of variables.
We learned that there are two kinds of variables: independent
variables and dependent variables. Independent variables can
be explained as the cause, while dependent variables are the
effect of that cause. When there is manipulation in the
independent variable, there is a change in the dependent
variable.
The independent variable can be further divided into an active independent variable or an attribute
independent variable (Gliner et al., 2017). A variable that can be manipulated by the researcher is known as
the active independent variable. In a controlled experiment, this variable can be manipulated. For example, in
a dieting experiment, if the researcher changes the dieting regimen, then that variable is known as the active
independent variable.
A variable that cannot be manipulated by the researcher is known as the attribute independent variable. Even
in a controlled experiment, certain characteristics are beyond the researcher’s ability to manipulate, and such
characteristics describe an attribute independent variable. For example, the participant’s age, race, and
mental rigor fall beyond the purview of the researcher’s manipulation, and such characteristics describe an
attribute independent variable.
As human nature can be frail, there is always an inherent bias in selection. In order to reduce this bias, the
randomization method is used to select the sampling, and human intervention in selecting the participant
should be kept to a minimum. Randomization enhances the conclusion of the experiment overall.
(Plantfelicity, n.d.)
RCH 8301, Quantitative Research Methods 3
UNIT x STUDY GUIDE
Title
Quasi-Experimental Design
There are many areas where the randomized experimental designs cannot be used. To study such
conditions, quasi-experiments are considered a suitable alternate. In the researcher’s world, this model is
unscientific and unreliable as it does not carry the same rigorous standards of the experimental design.
Nevertheless, it can be used to measure huge sizes such as cross-cultural behaviors or public policy
effectiveness in similar communities.
In this design, the researchers can only observe the causal variable but are not able to manipulate it. These
types of research approaches are more realistic than the experimental designs as they reflect the real world.
Reactions of the test subjects are more realistic, and the outcomes can be closer to the answers. These
experiments reinforce the experiments in a controlled environment and can be used to increase its reliability.
However, they are more prone to human error. The bias is much more prominent than in the controlled
experiments (Price et al., 2015).
Nonequivalent Group Design
Nonequivalent group research design is one of the most frequently used in research where the researcher
does not assign these types of groups. When participants are not selected and controlled, the groups tend to
be more dissimilar. Nonequivalent groups can be defined as the groups where the participants are selected
nonrandomly and post-intervention studies are conducted. We try to select groups that are as similar as
possible so that we can fairly compare the treated one with the comparison one (e.g., average educational
qualifications across various cultures, effectiveness of public policies across similar income countries).
In nonequivalent group design, only one group is exposed to the treatment, and the other is not. When a new
intervention is made in an ongoing project, this method can be used to gauge the effectiveness of the
program. For example, a posttest intervention can be made to assess a new teaching method in a school. Its
outcome can be noted. If similar groups are selected for the experiment, it will increase the reliability of the
experiment and will reduce the confounding variables.
To increase the reliability and credibility of the posttest design, pretest and posttest intervention can be
introduced. A treatment group is given pretest and posttest intervention before and after the introduction of
the changes. The nontreatment group where no such change applies also can be given this intervention to
measure how effective the change is. For example, you could introduce a nutritional intervention scheme in a
school. The pretest and posttest design can bring out how the nutrition of the child improves the learning
outcomes of the child.
The time series research design takes measurements over a series of time. Data is gathered periodically in a
timely order, and the data consistency is checked. Time series design is relevant across various research and
observational studies, and the long-term deviation, impact, and change of a phenomenon can be measured.
Time series is a repeated periodical measurement that is taken across equally spaced time intervals. For
example, the level of rain across a region through various time periods can strengthen the climatic models.
The public policy’s health can be measured by analyzing its effectiveness. The data gathered when the policy
was introduced (i.e., how the landscape has changed in the midcourse and its lasting impact) can be
measured through the time series model.
Nonexperimental Research Design
Nonexperimental research is normally descriptive or correlational since variables cannot be manipulated, and
participants cannot be assigned randomly; therefore, no causal nature can be determined. The nature of the
research question determines whether the researcher chooses between an experimental and
nonexperimental research design. If the research question involves a causal relationship and an independent
variable that can be manipulated, the experimental approach is typically preferred. However, a
nonexperimental research design is preferred when there is a single variable being studied, when there is not
an active independent variable, or when there is a non-causal statistical relationship between variables.
Although nonexperimental research can be both quantitative and qualitative, our focus will be on the three
quantitative nonexperimental research approaches: descriptive, associational, and comparative. Many
RCH 8301, Quantitative Research Methods 4
UNIT x STUDY GUIDE
Title
research studies contain more than one hypothesis, so many use a combination of research approaches to
construct the hypotheses.
Internal validity
One factor in determining the quality of a research study is
its internal validity. Validity is a tool to measure whether the
intention of the research matches the outcome of the
research, and it measures how well an experiment is done. It
shows the confidence that can be placed in the cause-andeffect relationship in the research study. Internal validity
shows us how well a study is organized and executed to
prevent errors and bias. The internal validity’s scope is within
the research only and focuses on these issues:
 How well was the research done?
 Does it have confounding variables?
Internal validity and confounding variables share an
inversely proportional relationship. When the confounding
variables increasingly affect the outcome, the internal validity will be less. The higher the internal validity, the
higher the credibility of the research will be (Trochim, 2006).
There are a number of potential threats to internal validity. Threats, such as maturation (i.e., when the
participants in the study change over time) and history (i.e., when an event occurs beyond the researcher’s
control), affect the outcome of a study. Another influencing factor is testing, which is when participants do
better on the posttest than on the pretest due to the experience gained. Instrument occurs when there is
inconsistency between the last interview and the first one (Gliner et al., 2017). Therefore, it is important to
have a well-designed research study with high internal validity.
References
Gliner, J. A., Morgan, G. A., & Leech, N. L. (2017). Research methods in applied settings: An integrated
approach to design and analysis (3rd ed.). Routledge.
Hafakot. (n.d.). Data validity concept (ID 88877337) [Illustration]. Dreamstime.
https://www.dreamstime.com/stock-illustration-data-validity-concept-d-illustration-title-businessdocument-image88877337
Plantfelicity. (n.d.). Newton cradle, cause and effect concept, blue infinity Newton`s cradle 3d illustration
banner (ID 110665870) [Illustration]. Dreamstime. https://www.dreamstime.com/close-up-newton-scradle-newton-cradle-cause-effect-concept-blue-infinity-newton-s-cradle-d-illustration-bannerimage110665870
Price, P. C., Jhangiani, R., & Chiang, I. A. (2015). Research methods in psychology.

Quasi-Experimental Research


Trochim, W. M. (2006). Internal validity. Conjoint.ly. http://www.socialresearchmethods.net/kb/intval.php
Learning Activities (Nongraded)
Nongraded Learning Activities are provided to aid students in their course of study. You do not have to submit
them. If you have questions, contact your instructor for further guidance and information.
Review the “Interpretation Questions” and “Application Problems” at the end of Chapters 4, 5, 6, 7, and 8.
(Hafakot, n.d.)

 
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