Running Head DOCTORAL STUDY PROSPECTUS1DOCTORAL STUDY PRO.docx

Running Head: DOCTORAL STUDY PROSPECTUS
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DOCTORAL STUDY PROSPECTUS
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Doctoral Study Prospectus
Employee retention is the dream of human resource managers,
and this is especially if these individuals are also self-motivated
and competent (Paludi, 2012). Replacement and retraining of a
new workforce are always expensive and destabilizing, and the
organization might lose opportunities as it concentrates on the
remaining inadequate staff (De Clercq, Mohammad Rahman, &
Belausteguigoitia, 2017). James (2016) has identified
unresolved disputes as one of the main reasons why the turnover
rate is still significantly high among US-based organizations.
The proposed study is the ‘influence of dispute resolution on
employee retention,' and it will have a positive impact not only
just on the business community but also on the society in
general. Obviously, conflict within an organization manifests
itself according to the hierarchical, top-down power nature that
is found within a business, which affects how people view and
interact with others, how relationships develop, etc.Problem
Statement
The average employee turnover rate in the United States is over
15%, and it is over 20% in Canada. At least 63% of these
employees leave upon resignation, and another 30% get fired.
Such drastic measures are direct consequences of unresolved
disputes (Allen & Bryant, 2012). According to Santos,
Uitdewilligen, & Passos (2015), there is yet some significant
number of workers who are demoralized to the extent of being

underproductive. Therefore, the organization is still losing as a
result of escalated disputes even if the employees choose to
stay. But, as part of Allen and Bryant (2012) research into
conflict in organizations, the authors view organizational
conflict as a "Conflict of Needs" based upon the "Fight or
Flight" response. They actually are working on an ebook
regarding just this. The proposed study is geared towards
enabling organizations to half their turnover rate every quarter
until it is less than 5%. Effective dispute resolution mechanisms
would not only motivate employees but also dissuade the
workers from opting to resign (Santos et al., 2015; Torchia,
Calabrò, & Morner, 2015). The proposed study is geared
towards establishing the steps which the management would
take to ensure that a positive work environment is maintained.
Purpose Statement
Everyone has certain needs based on Maslow's Hierarchy of
Needs, which explains that all human beings have certain needs
that they wish to have met, people (even if unknowingly) desire
the ability to secure these needs. Similarly, employees also
often have needs which failure to get met triggers disputes and
conflicts among them (Aamodt, 2006). Disputes are expensive,
time-consuming and damaging. They need to either be prevented
or resolved as early as possible. The study seeks to establish the
correction between such follower characteristics as
agreeableness, competence, openness, and focus of control;
leader characteristics like agreeableness, extraversion,
contingent reward behavior and transformational leadership; as
well as interpersonal relationship factors like self-promotion,
assertiveness, perceived similarity, leader’s trust with the
consequences (Tong et al., 2018). The, in this case, is role
conflict, role ambiguity, affective commitment, and turnover
intentions. This is a quantitative study of United Health Group
Inc. which is a Minnetonka-based firm with over 270,000
employees spread across thousands of locations in the country
(James, 2016; Torchia et al., 2015). The findings will reveal

how firms can save resources, time and focus on the issues
which matter as far as sustainability is concerned. To achieve
the kind of goals desired, there has to be a settlement rate of at
least 85%.Nature of the Study
The mixed method of research facilitates a much broader
understanding of the issue at hand. Business research will
certainly make conclusions recommending focus of attention
and investment towards a particular direction. Therefore, the
study methods to be used in this study will include in-depth and
mixed methods. Besides, there will be an enhanced involvement
of stakeholders as opposed to merely treating them as statistics.
The study is also correlational and it is hoped to reveal strong
relationships. Since the pattern of behavior will be uncovered, it
will be possible to make predictions (Presbitero, Roxas, &
Chadee, 2016). The research intends to include large size
research respondents in this study since this will help to
increase the validity and reliability of this study (Creswell,
2013). There is also the chance to show how one kind of
behavior could happen in the presence of another. For instance,
Oleksiiovych (2018) notes that once the employees have
resolved to leave, they are likely to do it in a few months, even
if their grievances are addressed. This is because threating to
resign is the mark of severe desperation. The goal is to resolve
complaints way before when such kind of desperation has
emerged. Papenhausen & Parayitam (2015) opine that most
employees will turn a blind eye during the first few instances of
disagreements and only get concerned if it becomes a persistent
pattern. The study is meant to come up with a framework which
would help solve problems before it escalates and cause bitter
separation either through firing or resignation.
Central Research Question and Hypotheses
The research questions are about the three categories of factors
with the most significant influence on employee retention. The
hypotheses are based on the research question. The hypotheses
state the relationship between variables precisely.

The Research Questions
a. In what ways do the follower characteristics increase
employee retention?
b. To what extent do the leader characteristics solidify
employee rate of retention?
c. How do interpersonal relationships facilitate employee
retention?
Interview Questions
i. Have you ever found yourself in a fight with your fellow
colleague and what did you do to solve the fight?
ii. What are some of the issues you sometimes experience that
stress you up at your place of work?
iii. What can do if your supervisor quarrels you because of
coming to work late?
iv. Would you decide to quit your place of work when you
realize your fellow colleague was added salary but yours was
not added?
v. Have you ever thought of fighting your manager if he/she
calls you names?
The Research Hypothesis
i. If the follower characteristics are improved, then the rate of
employee retention would rise.
ii. If the leader embraces the right characteristics, then
employee retention would be increased.
iii. If certain interpersonal relationships are put in place, then
the rate of employee retention could improve.
Conceptual/ Theoretical Framework

Some managers prefer using the dual concern model of conflict
management to solve conflicts between their employees. The
dual concern model is defined as a conceptual perspective that
focuses of personal preferred methods to resolve conflict with
regards to the two main themes which include empathy and
assertiveness commonly referred to as concern for others and
concern for self respectively (Raines, 2013). Conflict
management refers to the practice of identifying and handling
conflicts in a fair, sensible, and efficient manner. An
organization has to have people who understand and know how
to deal with disputes (Raines, 2013). According to K.W.
Thomas and R.H. Kilmann, there are five main styles of
responding to and resolving conflicts. The management must
start with a situational analysis to understand the most
appropriate one in regards to ascertaining the employees’
success (Papenhausen & Parayitam, 2015). In essence, the
leaders and followers' characteristics, as well as the
interpersonal relationships; would inform if accommodating,
competing, avoiding, collaboration and compromising and this
would be the best conflict resolution approach. The envisioned
framework will help understand how stakeholders can engage
while focusing on events and behaviors, identify the areas of
disagreement and agreement, and prioritize on the regions of the
conflict. It is a development of the plan to work on every aspect
of the conflict (Camelo-Ordaz, García-Cruz, & Sousa-Ginel,
2015).The significance of the Study
This study would add new knowledge on the existing ones about
the organizational conflict management because conflicts often
begin an unhealthy dynamic that affects a person's perception of
the other and begins to activate their "Fight-or-flight" response
mechanism; this will ultimately affect how they respond to the
conflict is solution is not found at the right time. The choice to
either remain with the organization or quit is based on how
satisfied one is with their place of work (Baker & McKenzie.,

CCH Australia Limited & Macquarie University, 2010). This
happiness is significantly influenced by how disagreements and
are handled; and, indeed, a significant number of employees
would be loyal to their employers in spite a couple of hiccups,
as long as they can preserve a brighter future (Matitz &
Chaerki, 2018).Contribution to Business Practice
Organizations stand to gain if their workforces stabilize.
Frequent turnover means that the cost of retraining goes up, and
there is also the challenge of orientation and keeping the new
employees motivated. Any employee who joins an organization
which is infamous for a high employee turnover would be
worried. They would not optimize their potential since they
would always be searching for much better opportunities than
the ones they possess. Such organizations cannot attain and
maintain their leverage (Knights & McCabe, 2016). Therefore,
finding an effective way of keeping these employees with their
employer would be invaluable to the business community. This
is the goal of the proposed study.
The implication for Social Change
If the employees have a comfortable working environment, they
would be satisfied (Finnegan, 2012). They would go home
having the joy of having accomplished their responsibilities in
the best manner possible and also feeling supported. Such happy
employees would become happy fathers, relatives, members of
their community, and the citizens. As a consequence, a lot of
conflicts at home and with friends would be mitigated (Matitz &
Chaerki, 2018). Therefore, the proposed research has the
advantage of influencing social change positively.Review of
Literature
Gough (2010) argues that most conflicts originate from human
behavior dynamics, especially as it scales in size. The bigger
the organization becomes, the more bureaucratic the
management echelons become, and the more important

competent managers become. Corporate management probably
looks relatively simple to, say, an engineer or mathematician,
who are adept dealing with concrete laws and theories who can
be proven. According to Matitz & Chaerki (2018), conflicts are
always expensive. This is because instead of concentrating on
work, the employees participate, try to avoid, and seek to
manage pointless disagreements with their peers. Papenhausen
& Parayitam (2015) opines that Americans are spending 2.1
hours per week (or a day in a month) dealing with conflicts.
This translated to over 385 million workdays or a loss of about
$359 billion annually.
Paludi (2012) on the other hand, believes that the causes of
conflict are as numerous as there are stars in the sky.
Fortunately, the remedies are equally abundant albeit less
obvious. Skilled managers and leaders are the keys to success,
according to the author’s opinion. A capable leader is not
obsessed with conflict management in itself; rather, they realize
it can actually serve as a springboard for meaningful change.
Every organization, big or small, will stagnate if the change
(which is often viewed as conflict) is avoided at every turn.
Torchia et al. (2015) note that conflicts in the workplace is to
blame for over 25% of the reported cases of absenteeism and
sickness. Also, 9% of project failures are attributed to conflicts,
and Presbitero et al. (2016) argue that 33% of the employees are
quitting or getting fired as a consequence of unresolved
disputes. According to Tong et al. (2018), other costs include
disorienting the clients who witness the conflicts. These clients
can decide to source their goods and services elsewhere.
In regards to the turnover rate, Presbitero et al. (2016)
highlight, it is imperative to recognize that the cost of
replacement is high. It disorients the organization significantly,
and the sales lost during such instances of turbulence are
irreplaceable. Consequently, it is imperative to recognize not
only the conflict but also the need to have it addressed. De
Clercq et al. (2017) insist that management must find the ways

and means of rallying the workers behind a common objective.
As they do so, they also need to convince these workers of the
need to consider the views of one another (De Clercq et al.,
2017; Presbitero et al., 2016).
Allen and Bryant (2012) argue that change is often equal to
conflict. According to the author, human beings often like to
talk about change all the time, yet it tends to remain in the land
of the theoretical where it is quite comfortable for employees to
cope with. Real change, however, induces far more stress into
the system (Finnegan, 2012; Gough, 2010)). This stress,
paradoxically, is the real secret ingredient to the organizational
recipe. Too much or too little can actually be lethal to the
organism we call an “organization” leading to lots of babbling
up there. But do any of them actually name the precise types of
conflict; Finnegan (2012) believes them to be far more
numerous than his poor fingers and overworked brain cells
could possibly list off.
Raines (2013) names two: “Human behavior” and “Growth” as
the main source of stress within various organizations and
argues that an organization whether large or small must
experience growth and the inherent stresses hidden within.
Rapid growth sounds great, but it will also induce unforeseen
stresses into the system. These stresses will have a trickledown
effect on everyone right from the CEO to janitor thus the
alternative to growth is becoming extinction even though that
also sounds stressful. Fortunately, Baker and McKenzie., CCH
Australia Limited., and Macquarie University (2010) opine that
leaders and managers often know how to keep the little fires
contained so that the whole organization does not burn to the
ground. They also realize the importance of keeping the small
fires lit, as complacency is the death of innovation. They realize
that stress causes anxiety, which causes conflict. They also
realize we need a healthy dose of anxiety to bring out the best
in all of the employees. This balancing act is the holy grail of
business management.

Camelo-Ordaz et al. (2015) argue that some conflicts are caused
by incompetence, and hence the need to consider making
enhanced hiring decisions. For instance, an organization can
engage the services of a consultant who conducts personality
together with competency tests. It is also essential to consider
calling the references indicated (Oleksiiovych, 2018). Valuable
information could be revealed if such decisions are made.
According to Knights & McCabe (2016), a culture of training is
also motivating. It makes the employees feel that the
organization is planning for a long term relationship with them.
The training must include the strategies towards handing
conflicts.
Conclusion
Once the appropriate framework is established, it must become
a central pillar of the organization’s handbook. The handbook
might need to highlight the unacceptable behaviors; and these
include bullying, respect, privacy, and gossip. In essence, the
system for dealing with the conflict must be clearly outlined,
and the stakeholders must embrace a proactive approach in
handling disagreements when they arise (De Clercq et al., 2017;
Knights & McCabe, 2016). The authors believe that fear of not
getting needs met, fear of being seen as "wrong" or inadequate
and fear of having things becomes more difficult are among the
major reasons why employees might sometimes feel stressed up.
Another reason is the capacity to perceive others' points of view
which are often referred to as "emotional intelligence" (EI) or
simply "empathy." A common barrier to EI and empathy is a
belief that if we see the other person's viewpoint, we will have
to do something about it. This might make us believe we will
have to give up our own perspective (and therefore our own
needs and wants in the situation), or we might believe that we
will be perceived as weak if we demonstrate empathy - again,
each person has some variation on their fear of showing EI /
empathy thus leading to organization conflict. However, to
resolve these conflicts successfully, the organization

management must embrace dialogue and open door leadership
where all employees are given the opportunity to raise their
complaints, get heard and their issues solved.
References
Top of Form
Aamodt, M. G. (2006). Industrial/organizational psychology: An
applied approach. Princeton, N.J: Recording for the Blind &
Dyslexic.
Bottom of Form
Top of Form
Allen, D. G., & Bryant, P. C. (2012). Managing employee
turnover: Dispelling myths and fostering evidence-based
retention strategies. New York: Business Expert Press.
Top of Form
Baker & McKenzie., CCH Australia Limited., & Macquarie
University. (2010). Australian master human resources guide.
North Ryde, N.S.W: CCH Australia.
Bottom of Form
Bottom of Form
Camelo-Ordaz, C., García-Cruz, J., & Sousa-Ginel, E. (2015).
The influence of top management team conflict on firm
innovativeness. Group Decision & Negotiation, 24(6), 957–980.
https://doi.org/10.1007/s10726-014-9424-4
Creswell, J. W. (2013). Research design: Qualitative,
quantitative, and mixed methods approach. Sage publications.

De Clercq, D., Mohammad Rahman, Z., & Belausteguigoitia, I.
(2017). Task conflict and employee creativity: the critical roles
of learning orientation and goal congruence. Human Resource
Management, 56(1), 93–109. https://doi.org/10.1002/hrm.21761
Top of Form
Finnegan, R. P. (2012). The power of stay interviews for
engagement and retention. Alexandria, VA: Society for Human
Resource Management.
Bottom of Form
James, A.R. (2016). Because arbitration can be beneficial, it
should never have to be mandatory: Making a case against
compelled arbitration based upon pre-dispute agreements to
arbitrate in consumer and employee adhesion contracts. Loyola
Law Review, 62(2), 531–576
Top of Form
Gough, J. A. (2010). Consultants & consulting organizations
directory. Farmington Hills, MI: Gale / Cengage Learning.
Bottom of Form
Knights, D., & McCabe, D. (2016). The “missing masses” of
resistance: An ethnographic understanding of a workplace
dispute. British Journal of Management, 27(3), 534–549.
https://doi.org/10.1111/1467-8551.12170
Maritz, Q.R.S., & Chaerki, K.F. (2018). Process philosophy’s
potential contributions to innovation process research within
organization studies. Revista de Administração e Inovação -
RAI, 15(4), 386–393. https://doi.org/10.1108/INMR-08-2018-
0062
Oleksiiovych, L.Y. (2018). Modeling of socio-economic

relations in scientific research processes. The economy of AIC,
(2), 5–13 Top of Form
Paludi, M. A. (2012). Managing diversity in today's workplace:
Strategies for employees and employers. Santa Barbara, Calif:
ABC-CLIO.
Bottom of Form
Papenhausen, C., & Parayitam, S. (2015). Conflict management
strategies as moderators in the antecedents to effective conflict
and its influence on team effectiveness. Journal of Business &
Management, 21(1), 101–119
Presbitero, A., Roxas, B., & Chadee, D. (2016). Looking beyond
HRM practices in enhancing employee retention in BPOs: Focus
on an employee–organization value fit. International Journal of
Human Resource Management, 27(6), 635–652.
https://doi.org/10.1080/09585192.2015.1035306Top of Form
Raines, S. (2013). Conflict management for managers:
Resolving workplace, client, and policy disputes. San
Francisco: Jossey-Bass.
Bottom of Form
Santos, C.M., Uitdewilligen, S., & Passos, A.M. (2015). Why is
your team more creative than mine? The influence of shared
mental models on intra-group conflict, team creativity, and
effectiveness. Creativity & Innovation Management, 24(4),
645–658. https://doi.org/10.1111/caim.12129
Tong, S.F., Ng, C.J., Lee, V.K.M., Lee, P.Y., Ismail, I.Z.,
Khoo, E.M., … Abdullah, A. (2018). Decision-making process
and factors contributing to research participation among general
practitioners: A grounded theory study. PLoS ONE, 13(4), 1–17.
https://doi.org/10.1371/journal.pone.0196379
Torchia, M., Calabrò, A., & Morner, M. (2015). Board of

directors’ diversity, creativity, and cognitive conflict.
International Studies of Management & Organization, 45(1), 6–
24. https://doi.org/10.1080/00208825.2015.1005992
06276 Topic: PSY 325 Statistics for the Behavioral & Social
Sciences Instructor: Nikola Lucas
Number of Pages: 4 (Double Spaced)
Number of sources: 4
Writing Style: APA
Type of document: Essay
Academic Level:Undergraduate
Category: Physics
Language Style: English (U.S.)
Order Instructions: Attached
please answer the questions with comments for all the names in
the order.
thank you and God Bless
Week 3 - Discussion
66 unread replies.66 replies.

Your initial discussion thread is due on Day 3 (Thursday) and
you have until Day 7 (Monday) to respond to your classmates.
Your grade will reflect both the quality of your initial post and
the depth of your responses. Refer to the Discussion Forum
Grading Rubric under the Settings icon above for guidance on
how your discussion will be evaluated.
ANOVA
In this discussion, you will evaluate a research question and
determine how that question might best be analyzed. To do
this, you will need to identify the appropriate application of
course specified statistical tests, examine assumptions and
limitations of course specified statistical tests, and
communicate in writing critiques of statistical tests.
A researcher wishes to study the effect of a new drug on blood
pressure. Consider and discuss the following questions as you
respond:
· Would you recommend using a z-test, a t-test, or an ANOVA
for the analysis? Explain your answer.
· What would your choice of test depend on? For the test you
select, explain your design and your comparison groups.
· Would the hypothesis be directional or non-directional?
· Would the test be one-tailed or two-tailed?
· What would be the null and what would be the alternative
hypothesis?
Guided Response: Review your classmates’ posts. Respond to
at least three of your classmates. Do you agree or disagree with
the test selected by your peer? How does the number of groups
being compared affect the statistical analysis? What suggestions
would you make for change or improvement? Why would these
suggestions potentially be more useful?
PLEASE MAKE COMMENTS IN EACH NAME OF PERSON
AS SHOWING, ALSO GIVE EXAMPLE OF THE
DISCUSSIONS WITH MATH WITH REFERENCE AS WELL.
Week 3-Discussion

Brenda Kyle;
Would you recommend using a z-test, a t-test, or an ANOVA for
the analysis? Explain your answer.
I would use the ANOVA for testing's because from what I
read on, and it would be the most accurate. The commonplace
information structure for use with an ANOVA requires the free
factor to be clear cut, and the reaction to be numerical.
Concerning your improvement reaction bend, the upgrade would
need to be clear cut, either ostensible or ordinal. In light of your
depiction of the improvement, I will expect that it is all out
ordinal. The reaction that you're trying, regardless of whether it
be the estimation of some phenotype or a learning time for 2
distinct creatures, must be numerical.
What would your choice of test depend on? For the test, you
The information must be regularly circulated as to the
testing appropriation, and the information must show
homoskedasticity - having a standard deviation that is
indistinguishable from or like that of different gatherings inside
the example. An ANOVA must be utilized under a specific
arrangement of conditions: It must be sensible to accept that the
information was acquired through an irregular example of an
enormous populace and that the information is free concerning
every one of the people focuses and every class.
Would the hypothesis be directional or non-directional?
I think it could be non-directional. Directionals theories
was utilized as past researches recommends about the
discoveries on an investigation that goes with an specific
course; nonetheless, within the concentrate has said that
therapist did not know about some past studies, directional
speculation wasn't suitable (Tanner, 2016).
Would the test be one-tailed or two-tailed?
In respect to the improvement reaction bend, you will in all
probability need a 2-way ANOVA. The reaction can be ordered
by both creature type and treatment, giving you 2 straight out

factors. It is proper to utilize an ANOVA with this information,
even though I suggest utilizing an elective test on the off chance
that you have 2 factors to work with.
What would be the null, and what would be the alternative
hypothesis?
I think using ANOVA would be the best solution to solve
all the issues. If I were doing the blood pressure pill studies, I
would have 2 different groups to research. One group would
have the actual blood pressure pill while the other group has the
placebo pill. Both groups would not know who had what and
then I world survey them all on how they are feeling.
According to the textbook any event, R. A. Fisher (Tanner,
2016) are available within production on the present-day factual
examination. Among the twentieth century, he were employed
by an agrarian researchers headquarters. Breaking down an
impact on the poison along with composts onto the harvest's
amounts, that hindered from the autonomous t-tests (Tanner,
2016) were enabled the researcher thinking about just 2
examples at once. Among that push for suit increased
examinations, he made an investigation on variance that is
called ANOVA (Tanner, 2016).
References
Tanner, D. (2016). Statistics for the Behavioral Social Sciences,
2nd edition. Bridgepoint
Education
Nikola Lucas
Hi Brenda,
First I want to commend you on being the brave student to
comment first on the post. Your research design ideas are good;
however the ANOVA is not necessary for this analysis. ANOVA
is used with 3 or more groups. If you only have two groups, a t-
test is appropriate. In addition, every study has both a null and
alternative hypothesis. At the conclusion of the experiment, the
statistical results determine which hypothesis has been
supported.

Reply to Comment
·
Christa Girard
Hello Dr. Lucas,
I understand the question now that I have read your feedback
and will add to my post. I was kind of on the same page as
Brenda. Thanks for the clarification.
Christa Reply to Comment
Brenda Kyle
Hi Professor,
The null hypothesis were an hypothesis were no measurable. A
null hypothesis is a hypothesis that says there is no statistical
significance between the two variables. It is usually the
hypothesis a researcher or experimenter will try to disprove or
discredit. An alternative hypothesis is one that states there is a
statistically significant relationship between two
variablescentrality between the two factors. It is normally the
hypothesis a analyst or experimenter will attempt to invalidate
or ruin. An alternativehypothesis is one that states there is a
measurably critical connection between two factors (Tanner,
2016).
Brenda Reply to Comment
Christa Girard
Hello Brenda!
After using the online tutor I have a better understanding of
when to use the different tests. T-tests are used for studies that
have two groups, Z-tests are used for studies that have more
than 30 groups and ANOVA is used when the number of groups
being tested lies between 2 and 30. Originally, I had added a
group that was not necessary. I considered having a high dose
group, low dose group and placebo group so I had said that
ANOVA was the best to use but after reading Dr. Lucas'
feedback on your post I now understand that the t-test is best to

use for this analysis because you only need the two groups:
group that was given the blood pressure medication and the
group that was given the placebo.
We will figure this out!!!
Good luck!
Christa Reply to Comment
Christa Girard
Hello Class!
For this analysis I would use ANOVA because there would be 3
groups to cover the hypothesis as well as the limitations in the
study. The 3 groups consist of a group that receives a high does
of the medication, a group that receives a low dose of the
medication and a group that receives a placebo.
What would your choice of test depend on? For the test you
select, explain your design and your comparison group.
The choice of test would depend on how many groups there are.
T-tests require the use of 2 groups, Z-tests require over 30
groups being studied in a group and the use of ANOVA for
analysis would be the number of groups totaling in between 2
and 30 groups. For this test I selected using ANOVA for
analysis because I am considering the use of three groups being:
a high dose of the blood pressure medication having the most
effect out of the three groups, a low dose of the medication
having somewhat of an effect and a placebo group having little
to no effect at all
In the test I would be conducting directional because I am
assuming that the amount of medication given will have have an
affect on the blood pressure readings after the medication has
been given. I am assuming that the group given the higher dose
will show the most change in results.
Would the test be one-tailed or two-tailed? This test would be
considered to be one-tailed and this is because there will be one

outcome which is the medication will have an effect on the
blood pressure readings.
What would be the null and what would be the alternative
hypothesis?
The null hypothesis would be there is no statistical difference in
the results of the three groups. The alternative hypothesis would
be that there is a statistical difference within the three groups.
The alternative hypothesis could be based on using the t-test
analysis with having only two groups: one dose of the blood
pressure medication and then the other group only receiving the
placebo rather than adding the third group like I did in my
study.
Reference:
Tanner, D. (2016). Statistics for the Behavioral & Social
Sciences (2nd ed.). San Diego, CA:
Bridgepoint Education, Inc.
Angela Gardiner
ANOVA Analysis
Considering the Nature of the question, I would go for the
ANOVA test. It is because to analyze the effects of the
introduction of a new drug to Bp; there is a possibility of other
factors that are likely to affect this test they, therefore, need to
be included. In the event, for example, I used a t-test, this
would only limit me two variables, and this would pose a
problem on how to analyze another variable. However, when
ANOVA is used, even if the independent variable is more than
two, such as three, all these independent variables can be
analyzed. There are indeed some commonalities that exist
between ANOVA and t-test, but when we consider doing the

analysis that will include more than two variables, then ANOVA
stands to be a more robust statistical test to use (Tanner, 2016).
Another reason why I would suggest the use of the ANOVA is
that, when research or study involves the study of human
beings, there is a likelihood of some level of error variance that
is expected. In this scenario, t-test or z-test cannot be in a
position to take care of the eventualities, and the only statistical
test that can be able to address such issue is ANOVA.
Lastly, would suggest the use of the ANOVA because, in case
of any variations in the problem under study, ANOVA is at a
position to address them. Example; A study carried to establish
cognitive effects of the Risperidone in Children with Autism
and Irritable Behavior; with several variations/independent.
However, variables are to be pronounced such as attention
effects, spatial working memory, acute safety, and long-term
tolerability and many other which can make all ripple from one
single question of analysis and all these can be addressed using
ANOVA (Aman et la…, 2008).
What would your choice of the test depend on? For the test,
you select, explain your design and your comparison groups.
The main factor that would guide me in selecting the test to use
would be the size of the population. For example, if the
population under study is too large, it would demand that it be
divided into subgroups, and this means I will have several
samples that will need to be studied. In such a scenario, the test
statistics that would use and give and provide accurate answers
that can be relied upon would be ANOVA (Tanner, 2016).
Perhaps is because ANOVA can be sued where analysis involves
more than two independent variables which are not possible is t-
test is used.
Considering the type of question that is we have, the most
appropriate hypothesis that can be used in this case would be
unidirectional. If the new drug is introduced, one question that

needs to be asked would be whether it would decrease or
increase the blood pressure, and this transforms the hypothesis
to be unidirectional.
Considering the above responses to question three, the test
statistics that will be sued would be a one-tailed test. Maybe it
is because, when we have a unidirectional hypothesis, a one-
tailed test is used, and when we have nondirectional hypothesis
two-tailed test is applied.
What would be the null, and what would be the alternative
hypothesis?
Depending on the response to qustion3-unidirectional
hypothesis would be used and question four that one-tailed test
would be used and question one that the suggested statistical
analysis would be ANOVA, the following would be the
hypothesis: Ho: µ0=µ1=µ2 and H1:µ0≤µ1≤µ2, that null
hypothesis and alternative hypothesis respectively(Tanner,
2016).
References
Aman, M. G., Hollway, J. A., McDougle, C. J., Scahill,
L., Tierney, E., McCracken, J. T., ... & Cronin, P. (2008).
Cognitive effects of risperidone in children
with autism and irritable behavior. Journal of Child
and Adolescent Psychopharmacology, 18(3), 227-236.doi:
http://dx.doi.org/10.1089/cap.2007.0133. It is retrieved from the
ProQuest database.
Tanner, D. (2016). Statistics for the Behavioral and Social
Sciences (2nd ed.) San Diego, CA: Bridgepoint Education, Inc.
Reply to Comment
Nikola Lucas
Hi Angela,
You correctly noted that when you have more than 2 groups, it

is most appropriate to use an ANOVA instead of a t-test. You
also noted that it is possible to examine several independent
variables at a time. What would be the problem with performing
multiple t-tests instead of a single ANOVA?
Reply to Comment
Shardae Rue
Hi Angela, really enjoyed your post. I definitely can understand
why the ANOVA test would be used. There are many variables
to consider especially while trying to answer the effects
medicine has on and blood pressure alone. We have to
determine the type of people we're examining whether it's male
female or both. Health conditions and risk we are looking for
and age. With all these different factors mentioned, you would
definitely have more than two sample groups. This test would
be perfect. What kind of design would you use to compare your
data? "One dependent-groups test where the same group is
measured twice is called the before/after t test. An alternative is
called the matched-pairs t test, where each participant in the
first group is matched to someone in the second group who has
a similar characteristic", (section7.2, para 3).
References
Sciences (2nd ed.). San Diego, CA, Retrieved from: Bridgepoint
Education, Inc.
Christa Girard
Hi Angela!
I enjoyed reading your post very much! It helped me to gain a
better understanding of this week's discussion. I like how you
pointed out that you chose to use the ANOVA test because of
the error of variance that is likely with the study being based on
human beings. It would make sense that this would be the only
analysis to apply to the study.
Great post!
Christa

Rickey Gray
respond:
My recommendation would be using a t-test. T-test is a
statistical hypothesis test. t-test compares the mean and
standard deviation of two samples to see if there is a significant
difference between them. T-test is most commonly used
Statistical Data Analysis procedure for hypothesis testing since
it is straightforward and easy to use. Additionally, it is flexible
and adaptable to a broad range of circumstances. T-test is more
adaptable than Z-test since Z-test will often require certain
conditions to be reliable.
The T-test is a test a of statistically significant difference
between two groups. A t-test compares the means of two
groups. For example, compare whether new blood pressure drug
differs between a control and treated group, between women and
men, or any other two groups. The t -test compares one variable
(blood pressure) between two groups.
Non-directional hypothesis predicts that two groups will be
different; but doesn’t say in what direction. Non-directional
hypothesis is used to prove that changing one variable has an
effect on another variable. It does not ask whether the effect is
positive or negative. Using the scenario provided we were
trying to see the effects of a new drug on blood pressure.
Two-tailed hypothesis tests are also known as non-directional
because you can test for effects in both directions. When a two-
tailed test is performed, the significance level percentage is
split between both tails of the distribution. An advantage of two

tail test is the ability to detect both positive and negative
effects. Two-tailed tests are standard in scientific research
where discovering any type of effect is usually of interest to
researchers.
hypothesis?
Null Hypothesis: There is no significant difference between the
blood pressure before and after new drug blood pressure
treatment; the difference we see in the means of the two
groups may be due to chance and sampling error.
Alternative hypothesis: There is a significant difference
between the blood pressure before and after new drug blood
pressure treatment; the difference we see in the means of the
two groups is mostly likely not due to chance or sampling error.
References:
du Prel, J. B., Röhrig, B., Hommel, G., & Blettner, M. (2010).
Choosing statistical tests: part 12 of a series on evaluation of
scientific publications. Deutsches Arzteblatt International,
107(19), 343–348. doi:10.3238/arztebl.2010.0343
Sciences (2nd ed.) San Diego, CA: Bridgepoint Education,
Inc.Reply to Comment
Shardae Rue
Hi Ricky,
It's nice to see someone else choose the t test. I'm pretty sure I
made this assignment, a little bit more complicated than it had
to be. I went on to try and solve my own hypothesis. In my
sample I use the paired t-test. I had one sample size but three
separate measurements. With that being said I used one tailed
test. I see that you have three separate samples with possibly
three separate three or more measurements. Do you believe that
the ANOVA test would be better. According to Tanner
(2016)"The difference is that in the independent t test the IV
has just two groups, or levels, and ANOVA can accommodate

any number of groups more than one",(section 6.1,para 3)
This part had me confused on which one to choose. Seemed like
a safe bet for small and large groups.
References
Sciences (2nd ed.). San Diego, CA, Retrived from: Bridgepoint
Education, Inc.Reply to Comment
Rickey Gray
Sharde,
Thank you for your post and your valuable feedback. ANOVA
test hypothesis that is appropriate to compare means of a
continuous variable in two or more independent comparison
groups like in a research studies where there are more than two
comparison groups. In a research study to evaluate a new
medication for asthma, researcher might compare an
experimental medication to a placebo and to a standard
treatment (i.e., a medication currently being used. The ANOVA
technique applies when there are two or more than two
independent groups. The fundamental strategy of ANOVA is to
systematically examine variability within groups being
compared and also examine variability among the groups being
compared.
Korrean Wright
In a study of a new drug on blood pressure, I would recommend
the researcher using a one-way ANOVA for the analysis because
this test would only involve one independent variable that
would determine the difference between any number of groups
(Tanner, 2016).
The one-way ANOVA test would depend on the population's
gender and culture. The comparison group would be three

samples of men and women of different cultures from the same
population. Preferably they would attend the same doctor's
office and all suffer from hypertension. The first group would
be administered 5 milligrams of the new drug daily, the second
group 10 milligrams, and the third group a placebo pill (all
groups would think that they were taking the new drug). The
groups will have their blood pressure taken three times a day
and recorded for two weeks then bring their results to their next
appointment.
The hypothesis would be directional because I would want to
predict change or a difference for the better. The test would also
be one-tailed because the test would indicate a prediction
(Tanner, 2016).
The Null Hypothesis: What effect will this new drug have on
hypertension? Is the difference for men as to women and will it
be effective for different cultures?
The Alternate Hypothesis: To test whether the new drug will
lower each gender and every culture or only some.
Reference
Glenn Caplan
Considering a study that a researcher wishes to conduct about
the effects of a new blood pressure medicine, I would choose to
conduct an analysis of variance (ANOVA). Unlike a t-test, an
ANOVA can be utilized to compare two or more groups (usually
at least three groups). An ANOVA is used to test a research
hypothesis and the null hypothesis. An ANOVA is also used to
compare between groups variability to within groups variability.
Statistics Articles (n.d.) notes that between groups variability is
variability from one group to another and within groups

variability is variability within one population. An ANOVA is
used to measure the sum of squares which simply means, the
sum of the squared values. A researcher would get the same
results if they conducted multiple t-tests. However, an ANOVA
not only compares the means, it examines the variation when
calculating the means.
I chose an ANOVA because I find that three groups would be
necessary for this type of study. The three groups involved
would need to be taken from a population with the same mean.
The three groups in the test would have a group receiving the
recommended dosage, the group receiving a small dosage, and a
group receiving a placebo that does not affect blood pressure
one way or another. After completing the study and computing
the F ratio (treatment variance divided by error variance), the
difference among the group will be discovered (Tanner, 2016).
The larger the F ratio, the more likely the differences between
the groups are less random. If the F ratio is small, it would
indicate that the medicine may not work that well. Tanner
(2016) reported that after the ANOVA is completed, the results
indicate the sources of variance, the sum of squares values, the
degrees of freedom, the mean squares values, and F.
The hypothesis would be considered directional because the
researcher would make a prediction regarding a positive or
negative effect (Directional Hypothesis, 2012). The entire idea
of this study is to understand if the medication affects the
sample from the population's blood pressure. Keywords that
indicate a directional hypothesis are higher, lower, increase,
decrease, positive, or negative (Directional Hypothesis, 2012).
If a non-directional hypothesis was chosen, the researcher
would not predict the kind of effect that occurs, but that there
is, in fact, some sort of effect.
Since the researcher wants to measure one direction, a one-

tailed test would be used to test the hypothesis. A one-tailed
test is used to determine whether the sample mean is higher or
lower than populations mean. The results can indicate if the
medication has either a positive or negative effect on the
sample, but not both like a two-tailed test could.
hypothesis?
In an ANOVA, the null hypothesis indicates that three samples
were drawn from the population with the same mean (Tanner,
2016). The alternative hypothesis changes a bit because three
groups do not have one potential alternative. Tanner (2016)
stated that sample one population mean value differs from the
other samples, sample one and two represent a different mean
than the population from sample three, and sample one and
three represent a population with a mean value different from
sample 2.
References
Directional Hypothesis. (2012, December). Retrieved from
http://methods.sagepub.com/reference/encyc-of-research-
design/n114.xml
Statistics Articles. (n.d.). Retrieved from
https://www.statisticstutors.com/statistics-ANOVA.html
Inc. Reply to Comment
Shanara Clay
pressure.
To study the effect of a new drug on blood pressure I would use
an ANOVA. An ANOVA is also known as an analysis of
variance and can accommodate any number of groups more than
one (Tanner, 2016). Using this statistical method would be the

most helpful since it allows researchers to answer some of the
same questions a t-test would, like if there is a difference in the
effects of the new drug. But the t-test wouldn’t be the best
method to use since there is room for error which is about 5%
on average and only increases the more test are added. So, using
multiple t-test is therefore not a good option (Tanner,2016).
It would depend on the number of groups/variables included in
the study. If there are two or less groups, I would use the t-test
to explain and compare. If there are three or more groups, I
would then use the recommended ANOVA since any number of
groups could be used and tested. To me the ANOVA method is
more realistic when conducting a research study since a bigger
sample size equals reliable results. Sample size is something I
would look for before accepting the effects of the blood
pressure medicine presented by researchers.
Would the hypothesis be directional or non-directional? Would
the test be one-tailed or two-tailed?
Since I am using an ANOVA the, hypothesis would be non-
directional. There was no specific direction researchers stated
they wanted the test to go so we should be aware the reasoning
is due to researchers not being unaware of the effects of the
blood pressure medicine; in this case the test would need to be
two-tailed. Plus, there was no specific prediction given about
the direction or differences in the hypothesis tested. So, because
of the vagueness and to be on the safe side I would stick with
two tailed test to show the relationship no matter direction.
hypothesis?
Null hypothesis- Blood pressure is not effected with the use of
this new drug designed to treat blood pressure for any of the
participants.
Alternative hypothesis- Blood pressure for more than half of the
participants were positively affected by using the new drug.
According to our textbook the null hypothesis predicts that the

result will not be statistically significant: that there is no(null)
difference between the population that the sample represents
and the population to which it is compared. The alternate
hypothesis
predicts that the result will be statistically significant: that there
is a difference (Tanner, 2016).
Reference
Sciences (2nd ed.). San Diego, CA: Bridgepoint Education, Inc
Reply to Comment
Christa Girard
Hello Shanara!
I was very confused on the directional/non-directional part of
this question so I used the online tutor and they explained it to
me as the if your hypothesis was basically looking for an
outcome then this would be direction, setting a direction for
your hypothesis to go in. I was stating that I thought the
medication would have an effect so I chose that it would be
directional. Your post also makes sense tho because we are not
sure what is going to happen.
I'll figure this out eventually!
ChristaReply to Comment
Glenn Caplan
Hi Shanara,
I enjoyed reading your post and thought you did a very nice job
presenting your information. I took some additional knowledge
away from your post so that is always a plus as well. I didn’t
realize that errors raised when additional t-tests were added. I
also selected an analysis of variance (ANOVA) due to similar
reasoning. However, I chose my hypothesis to be one-tailed and
directional due to the subject matter. I think this is because we
perceived the questions a bit differently. The way you state the
information made complete sense to me, but I would have still
stuck with my original choice. I also agree with your take on the

null and alternative hypothesis. Great work and good luck with
the rest of this week.
Joe Reply to Comment
Esther Landsberg
respond:
I would say that they should either use ANOVA or a t-test for
the analysis depending on how many groups they are comparing.
If it is only one or two groups, then they should use the t-test;
but if they are comparing three or more groups, then they
should use ANOVA (Tanner, 2016). The question does not
mention the amount of groups that will be compared so I will
assume that there will be just one or two groups and therefor a
t-test should be used.
The t-test will help get the means from the groups so we can
compare them (Tanner, 2016). Using the t-test will help
compare the variable of the blood pressure between the groups
of the study.
I think the hypothesis would be non-directional.
I think the test would be two-tailed.
hypothesis?
The null hypothesis would be that after the new drug, there isn't
really much of a difference in the blood pressure and any
difference shown would be because of sampling error. The
alternative hypothesis would be that there is a big difference in
the blood pressure after the new drug and any difference shown
is not because of sampling error, but because the drug

worked. Reply to Comment
Reference:
Sciences (2nd ed.). San Diego, CA: Bridgepoint Education, Inc.
Reply to Comment
Rickey Gray
Esther,
I enjoyed reading your post and I must admit when completing
my discussion response I was undecided about which test to
select. After reading the course material I selected the t-test.
The independent sample t-test compares the means of two
independent groups in order to determine whether there is
statistical evidence that the associated population means are
significantly different. The independent sample t-test can only
compare the means for two (and only two) groups. It cannot
make comparisons among more than two groups. If you wish to
compare the means across more than two groups, you will likely
want to run an ANOVA.
Sciences (2nd ed.) San Diego, CA: Bridgepoint Education, Inc.
Rickey Reply to Comment
Shardae Rue
Variables
The type of test we choose depended on the type of data we
collect, the group size and independent/dependent variables. We
want to know if a new drug has an effect on blood pressure.
Blood pressure is categorized as continuous data because blood
pressure rates vary based on the person and activities. The
independent variable in this study would be the new drug and
the dependent variable blood pressure.
Hypothesis, one-tailed, Null and Alternative
The initial aim states "A researcher wishes to study the effect of

a new drug on blood pressure". " Effect" and "on" are the
keywords that let me know that this statement is non direction.
Another word that would indicate nondirectionally is
"difference".
My hypothesis - New medication has an effect on blood
pressure because it decreases the blood pressure. This
hypothesis is directional so I would us one-tailed test.
Null hypothesis:
The mean difference is less than or equal to 0
Alternative hypothesis:
The mean difference is not less than or equal 0
Test and Design
If I have three people that all took the same new medication but
their blood pressures were all different, I would have one
sample (groups) and three measurements. Because I am
comparing three separate measurements I would use a paired t-
test. I would also use the before and after design.
Let say it a 30-day trial. I will take each blood pressure to
collect a baseline before the medication and take another blood
pressure 30 days after starting medication. In this study, I only
measured the diastolic number because it gives an indication of
heart attack or stroke risk when the numbers are high.
1. 160 after 150= 10
2. 145 after 134=11
3. 133 after 125=8
Mean difference =29÷3= 9.6
Because the mean difference is in more than 0 my hypothesis is
true.
Reply to Comment
Shardae Rue
My one sample group consist of three women only. So my
hypothesis would state new medication has an effect on
women's blood pressure because it decreases their blood
pressure.
Reply to Comment

Christa Girard
Hello Shardae!
I also chose that my test would be directional as my hypothesis
was that the medication would have an effect on the blood
pressure readings. In other terms, I was basically stating that I
was expecting this outcome to be achieved.
Thanks for sharing! Reply to Comment
Heather Nolan
respond:
I would recommend using an ANOVA for the analysis. ANOVA
allows the researchers to compare more groups, comparing the
amount of variation between groups with the amount of
variation within groups.
Size and the desired outcome would help to determine the
testing method used. When conducting this study, I would
divide the participants into groups depending on age, stress
level, and sex. It would be important to monitor the effects of
the medication both negative and positive.
The hypothesis would be non-directional. The question asked by
the researcher’s askes if the “independent variable will have an
effect on the dependent variable, but the direction of the effect
is not specified” (Mcleod, n.d.)
This would be a two-tailed test. Because the study is being
conducted to study the effect of a new drug on blood pressure it
is important to know the effect in both directions. It is
important to log the effects, both good and bad, of this new
drug. Using statistical tests inappropriately can lead to invalid

results that are not replicable and highly questionable (HOME,
n.d.).
hypothesis?
The null hypothesis could be that all of the individuals
participating in the study are white males, fair health, ages 40-
50. The alternative hypothesis could be that the groups tested
are as follows: females, high BP, age 55-60; males, low BP, 45-
50; males, moderate BP, 40-45.
References
HOME. (n.d.). Retrieved June 20, 2019,
from https://stats.idre.ucla.edu/other/mult-pkg/faq/general/faq-
what-are-the-differences-between-one-tailed-and-two-tailed-
tests/ (Links to an external site.)Links to an external site.
Mcleod, S. (n.d.). What is a hypothesis? Retrieved June 20,
2019, from https://www.simplypsychology.org/what-is-a-
hypotheses.htmlReply to Comment
Sandrene McFarlane
When evaluating the question regarding a researcher wanting to
conduct a study to determine the effects of a new drug on blood
pressure; I would recommend using the independent t-test for
analysis since it determines if two samples are from the same
populations and if their mean is the same (Tanner, 2016). This
method of analysis will reveal if the new blood pressure
treatment that was given to one group had a different effect on
their blood pressure when compared to the second group.
My choice of test would depend on the hypothesis being tested,
sample sizes or groups needed, and how the results would
represent the population. I started by determining what the
researcher was trying to prove, and I concluded that he/she was
trying to investigate whether the new blood pressure medication
lowered or increased the participant's results to show that there
are significant differences between the two groups data due to
the medication. To test this hypothesis, I believe that the study

would consist of one group with individuals who would take the
new drug or independent variable and a second group who
would take the previous method of treatment that was already
studied. Doing so would measure changes in blood pressure
levels between groups to see if there were increases or
decreases to values. Since this research contains two groups
used to measure the distribution differences for the population,
the independent t-test is essential (Tanner, 2016). This test
would also establish the standard errors and variability between
both groups (Tanner, 2016).
The hypothesis would be directional since it offers an alternate
prediction when introducing the independent variable (Tanner,
2016). Because this test is directional, it would be one-tailed; a
one-tailed t-test measures how one group varies from the other,
to test the range of difference based on the prediction (Tanner,
2016). Therefore, if the hypothesis was to show if the new
medication made the blood pressure reading lower or higher
than the other sample group, a directional one-tailed test is used
to show that the distribution is one-sided, meaning either an
increase or decrease in blood pressure levels will occur, but not
both. It fits what I believe the researchers are trying to prove.
A null hypothesis is used to show a lack of statistical
significance (Tanner, 2016). Knowing this I believe that the null
hypothesis for this analysis would be that the new medication
had no impact on blood pressure levels in the sample group, that
no change was noted to the population mean when introducing
this new variable, it remained the same. In contrast, since
the alternative hypothesis tries to prove the opposite of the null
to show differences in a population (Tanner, 2016). It would be
that the new blood pressure medication caused levels for the
population mean to change, resulting in an increase or decrease
readings. Overall, for this analysis, I believe that an alternate
hypothesis would be presented because I selected a directional
one-tailed independent t-test. According to Tanner (2016), if the
test is “one-tailed, the alternative hypothesis indicates the
direction of the predicted difference” (Section 5.4, “The

Independent t Test,” para.11). This outcome is what the
researcher is measuring — the differences between the means
after implementing the new blood pressure medication for that
population.
Reference
Sciences (2nded.) [Electronic version]. Retrieved from
https://content.ashford.edu/books/AUPSY325.16.
Reply to Comment
Mericka Franklin
In this case the t test can be of very important use. The t test is
another form of the ANOVA tests. This is because we might
have two or more means that we will compare (Tanner, 2016).
The first mean is the mean of the symptoms that are presented
by the patients with high blood pressure. The second mean is
the mean of values and symptoms of the group of people with
the high blood pressure who have used the drug. Therefore, to
determine whether there is a significant difference in the
characteristics between before the patients used the drugs and
the mean of characteristic of the patients after they took the
drug. In the situation of effect of drugs, we have to use the
mean of symptoms because every patient will react differently
to the drug.
For this test, I would have groups of comparison. We are
looking to use the drugs to ensure that patients’ characteristics
and symptoms are moving from those of the disease and moving
close to those of people without the disease. Therefore, once the
patients have taken the drugs, we look to see whether the
patients are moving away from the mean of symptoms of
patients with high blood pressure and moving towards the mean
of conditions of people without high blood pressure.
The hypothesis in this situation would be directional. This is
because the researcher has their own expectation on the drug to
work. The researcher will look to ensure that the drug will

work. Therefore, this test will have a have a directional
hypothesis. The test in this case would be two tailed. This is
because the drug can either lead to better results in the patient
or even in a worse situation. The test should therefore be two
tailed as it will look to see if the effects of the drug will be
positive or negative.
H0 : The drug reduces the effects of high blood pressure on the
patient
Ha : The drug does not reduce the effects of high blood pressure
on the patient
References
EducationReply to Comment
Yolanda Bias
Greetings Professor and classmates, I found this discussion
question to be very difficult but here are my responses to the
week discussion. I welcome all feedback that will help give me
a better understanding.
respond:
After reading through all of the choices and doing some
additional research I would choose ANOVA for testing. I am
not 100% sure of this because I do believe that all of the
options could test for the effects of the new medicine. My
reason for choosing ANOVA is because it can accommodate any
number of groups. More than one group would need to be
identified in this study. One group would be given the drug and
the other group would continue to take their prescribed blood
pressure medicine.

My choice of test depends on my population and being able to
measure all of the effects of the new drug as well as this differs
from what they were taking. I would have participants taking
the new drug and some still taking the prior prescribed medicine
to test out the difference. I believe this will allow me to see if
the new blood pressure medicine has a better effect than the
prior medicine.
I believe it will be directional. It will be measured against the
prior medicines to see which works best. It will predict how the
medicine from the first group is different from that of the
second.
I believe the test would be a one tailed test. Because it will
indicate a prediction of how the sample is expected to differ
from the population, rather than just assuming that the new
blood pressure medicine will work.
hypothesis?
The null would be that both the prior blood pressure medicine
and the new blood pressure medicine have the same effect on all
individuals. The alternative hypothesis is that the new blood
pressure medicine showed that it works better than the prior.
The new blood pressure medicine is more effective in helping to
manage blood pressure than the prior medicine used.
I had a rough time with this discussion and would really
appreciate feedback on where I went wrong or if I am on the
right track. Thanks everyone.
References
2nd edition. Bridgepoint Education Reply to Comment
Glenn Caplan
Hi Yolanda,

Nice job on your discussion prompt. I do not truly understand
everything either but with additional supports from internet
sites and videos on YouTube, I have been able to develop a
better understanding. This seems to be a tough subject for a lot
of us to grasp so just know that you are not alone in the
struggle. I also chose an ANOVA. You could conduct multiple
t-tests as well. With an ANOVA, you would need to conduct a
post-hoc analysis after F was deemed significant. I also chose a
one-tailed, directional hypothesis. Nice job and keep up the
good work.
Joe Reply to Comment
Susan Musgrave
ANOVA is used to compare means between three or more
groups. Using the t-test produces the possibility of sampling
error, and you have to have a sample of less than thirty (<30). I
would recommend the z-test in this particular study. To close
the margin of error, you would need a sample greater than thirty
(n>30). “Z test indicates how distant a sample mean is from the
mean of the distribution of sample means in units of the
standard error of the mean. When the value of z is 1.96 or
greater, there is a probability of p = 0.05 or less that the sample
belongs to the population” (Tanner, 2016, Glossary). If you are
going to test a new drug to see how it affects blood pressure,
you will need a sample sufficient enough to compare to a
distinct population. For the test selected, I would take a
population of one hundred men and women, all with high blood
pressure, dividing them into two groups, and giving one group
(1) the “real” pill and the other group (2) a placebo. The
hypothesis would be directional and one-tailed because they
only want to see the effects of the drug; does it work, or does it
not work. The null hypothesis is this drug works by lowering
blood pressure. The alternative hypothesis is it seems to work
only on women.
Reference

Sciences (2nd ed.). San Diego, CA: Bridgepoint Education, Inc.
Reply to Comment
Brian Perry
When looking at a study about the effects of a drug on blood
pressure, it can use a different method to analyze the data.
After looking at z-test, t-test and ANOVA as options, I have
come to believe the best option is ANOVA because it can
handle comparing multiple groups. It is a method of analyzing
the variance between groups within the samples. It basically
takes a statistical test like the one presented and looking to see
if the population means are equal. For this analysis, the
researchers could run multiple t-tests but that is not very
practical. It is important that when using ANOVA, that the data
is normally distributed or cleared any normality test.
What would your choice of test depend on?For the test you
ANOVA would depend on the difference between means for 2
or more groups. theo samples are equal, large, and normal. If
the groups only had 2 or less, then the t-test would be a better
fit. The only way a t-test would really benefit the data is if
groups are independent from each other. I believe that the
research of the new drug will need multiple groups to really
find accurate results for this statistical testing. The ANOVA
test also depends on the F ratio because it looks at the
difference in the different groups making sure the data is not
random.
The hypothesis would be non-directional because it predicts the
independent variable and how that impacts the dependent
variable. Directional Hypothesis may state how the results may
be predicted. However, non-directional will state that the
different groups may have different results that may result in

significant differences at the end. The research of drugs
impacting blood pressure is assumed to have multiple impacting
data.
Since non-directional hypothesis is used, a two-tailed test is
used because both sides of the rejection can happen on both
sides. This is important when the critical area of the
distribution is 2-sided. It is also impacted when the samples are
greater or less than range of values within a normal
distribution.
hypothesis?Null Hypothesis will present the data with no
difference between the different sample groups based on the
mean scores. This presents contradicting relationship between
the drug and blood pressure.
Alternative hypothesis, in contrary to the null hypothesis,
observations are resulted in a real effect. It is also known as a
maintained hypothesis. This would mean that their would be
difference between the blood pressure and the new drug being
implemented by any error in the sample.
References:
Reply to Comment
Glenn Caplan
Hi Brian,
Great job on your discussion post. I also chose an ANOVA due
to similar reasoning. Multiple t-tests would be impractical but
with an ANOVA, a post-hoc test would be necessary to
determine where the differences occurred between each sample
group. I chose a directional, one-tailed hypothesis but your
explanation seems accurate with the way you perceived the
questions. I am anxious to find out if I am correct in my
reasoning. I think that I am, but your explanation has me
doubting my reasoning a bit. Good luck with the rest of

this week's work and keep up the good work.
Joe
Section 1
Foundation of the Study
(FOR PROPOSAL & DBA DOCTORAL STUDY
DOCUMENTS)
Quality Indicators
Type Met, Not Met, or N/A in Each Cell
o. Ensures all numbers are expressed in digits (i.e., 1, 2, 10, 20,
etc.) and not spelled out unless beginning a sentence; Ensures
Abstract does not include seriation (i.e., (a), (b), (c), etc.).
(1.2) Background of the Problem9
Provides a brief and concise overview of the context or
background of the problem. DBA Doctoral Studies are focused
on applied business research. This sets the stage for the study.
This heading should comprise no more than one page in length.
(1.3) Problem Statement
Please review the video tutorial located @:
http://youtu.be/IYWzCYyrgpoto aid you in preparing the
Problem Statement.
a. Provides a hook10 supported by peer- reviewed or
government citation 5 or less years old from anticipated
completion date (CAO approval).
b. Provides an anchor11 supported by peer- reviewed or
government citation 5 or less years old from anticipated
completion date (CAO approval).
c. States the general business problem Note: This element
should start as follows: The general business problem is…

d. States the specific business problem. Be sure to state who has
the specific problem (i.e., small business leaders, project
managers, supply chain managers, etc.) Note: This element
should start as follows: The specific business problem is that
some (identify who has the problem)…
1.1 - ProblemStatement
As shown in the following graphic, the Problem Statement must
include four specific components the (a) hook, (b) anchor, (c)
general business problem, and (d) specific business problem. It
is recommended that the Problem Statement be approximately
150 words. More important, ensure the problem statement
reflects an applied business problem; avoid Rubric Creep45.
You must ensure you map to the rubric requirements. This is the
most critical component of the doctoral study and will be highly
scrutinized in the review process. Again, the Problem Statement
is not to identify causes for the problem, solutions to the
problem, or any other superfluous information. A well-written
problem statement can be presented in four to five sentences.
Please review the training video (see link below) developed by
the DBA methodology team to aid in writing your problem
statement. The video will help add clarity and save you time.
The Problem Statement Video Tutorial can be found at:
http://youtu.be/IYWzCYyrgpo.
45 Rubric creep occurs when the problem statement does not
reflect an applied business problem.
DBA students are seeking a degree in business and must ensure
the problem statement is business focused. The problem
statement must not represent a problem that has a social,

psychological, educational, or other discipline specific
emphasis. A business problem is something that is a problem for
a business from the perspective of the business managers or the
industry’s leaders. Therefore, it is important to adopt a
management perspective, and not that of social advocates. The
perspective must be from the position of the managers and
leaders of business who can address the problem.
Avoiding Rubric Creep
To ascertain if a problem addresses a business issue or has
Rubric creep/Rubric drift, please consider the following:
· An important indicator that a business related problem is a
specific business problem is that the problem statement relates
to a key business process that organizational leaders need to
address and effectively meet the organization’s mission.
· A business problem relates to one or more critical success
factors (CSFs). Business leaders use business processes to
function effectively to complete one or more CSF’s needed to
carry out their business mission.
· A business problem is one that a business manager/leader can
solve.
Conduct a final check of the problem statement by putting the
hook, anchor, general business problem, and specific business
problem in bullet form and check for alignment among the four
bullets. When you can ensure that the problem statement aligns
throughout, write in scholarly narrative form (no bullets).
Strategy for Mapping to the Rubric
· Read the rubric requirements for a heading.
· Read what you wrote in the heading.
· Read the rubric requirements for a heading again.
· Read what you wrote in the section and highlight (in the
proposal and the rubric) the rubric elements that you addressed
in the heading.

· Revise the heading as needed to include the rubric elements
that you missed and eliminate superfluous narrative.
· Start the process at the top again until you have mastered the
rubric elements in the heading.
Specific Business Problem
The specific business problem is the genesis of one’s study. It is
vital that one has a clear and precise specific business problem.
One will align the contents of the Research Question and
Purpose Statement with the specific business problem.
The qualitative specific business problem. The qualitative
specific business problem must be well defined and not contain
multiple issues (variables in quantitative studies). The
following graphic depicts how to include the elements needed in
a qualitative specific business problem.
The quantitative specific business problem. The quantitative
specific business problem must be well defined and contain the
key variables. The following graphic depicts how to include the
elements needed in a qualitative specific business problem.
Aligning the Specific Business Problem With the Purpose
Statement and RQ
Make certain that the specific business problem, Purpose
Statement, and Research Question (RQ) align. A good technique
to use to enhance the alignment is to put the specific business
problem, RQ, and first sentence of the Purpose Statement
together on a blank document to ensure that you are using the
same words. Notice the suggested order differs from the order
the headings appear in the study.

Qualitative alignment example. The graphic below provides an
example of alignment among the Specific Business Problem,
Research Question, and first sentence of the Purpose Statement
using the same key words. Pay attention to the words one uses
in identifying the issue that the leader lacks or has in limited
supply. The word determines how one can collect data.
· Some business leaders lack understanding… To ascertain what
one understands will require a quantitative design.
· Some business leaders lack knowledge… To ascertain a
business leader’s knowledge will require a quantitative design.
· Some business leaders lack strategies (or have limited plans,
processes, procedures)… To ascertain a business leader’s
strategies may involve interviews, focus groups, company
archival records and documents, company policies and
procedures, company intranet/Internet site, and
direct/participant observation (in some cases) to collect data.
Usually interviews or focus groups are the primary data
collection method.
· Some business leaders lack skills… To ascertain a business
leader’s skills will involve direct/participant observation as the
primary data collection method.
Quantitative alignment example. Notice how the Specific
Business Problem, Research Question, and first sentence of the
Purpose Statement use the same key words with the exception
that the research question and subsequent first sentence in the
purpose statement do not address the business leader—this is a
difference between qualitative and quantitative studies. The
following is an example of alignment for a quantitative
correlational study.

Hypothetical Example (Correlation Design) Problem Statement
Organizations place great emphasis on retention because of the
strategic value of intellectual capital and the costs of replacing
valued employees (cite)75. Research in this domain is
potentially valuable because turnover costs U.S. businesses
billions of dollars per year (cite), and practices that promote
retention can save even small companies millions of dollars
annually (cite)76. The general business problem is that turnover
intention has been shown to be among the best predictors of
turnover (cite)77. The specific business problem is that some
microelectronic business owners do not understand the
relationship between job satisfaction, motivation, and employee
turnover intentions78.
Hypothetical Example (Causal-Comparative Design)
Problem Statement
Organizations place great emphasis on retention because of the
strategic value of intellectual capital and the costs of replacing
valued employees (cite). Research in this domain is potentially
valuable because turnover costs U.S. businesses billions of
dollars per year (cite), and practices that promote retention can
save even small companies millions of dollars annually (cite).
The general business problem is that turnover intention have
been shown to have a significant impact on employee turnover
(cite). The specific business problem is that some micro-
electronic business owners do not understand the impact of job
satisfaction, motivation, on employee turnover intentions.

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