11 Sun Coast Remediation: Research Objectives, Research Questions, and Hypotheses 4 Sun Coast Remediation Unique R. Simpkins Southern Columbia University Course Name Here Instructor Name 11-2-2021 Research Objectives, Research Questions, and Hypotheses Based on the information amassed by the former health and safety director, the organization needs to pursue safety-related programs or initiatives to ensure employees' health. It is an appropriate approach to help the firm and the employees achieve goals and inhibit costs arising from injuries and illnesses while on duty. The completion of this task will provide managers with practicable insights on the approach to enhance safety and protect the firm from losses. This task accounts for the objectives, questions, and hypotheses of the research based on the provided statement of the problem. RO1: Explore the correlation between the size of the Particulate Matter (PM) and the health of the employee. RQ1: Is there a correlation between the size of the Particulate Matter (PM) and the health of the employee? Ho1: There is no statistically significant evidence connecting the size of the Particulate Matter (PM) and the health of the employee. Ha1: There is statistically significant evidence connecting the size of the Particulate Matter (PM) and the health of the employee. RO2: Establish whether safety training is feasible in decreasing the lost-time hours. RQ2: Is safety training feasible in decreasing the lost-time hours? Ho2: There is no statistically significant evidence linking safety training and reduction in lost-time hours. Ha2: There is statistically significant evidence linking safety training and reduction in lost-time hours. RO3: Establish the effectiveness of predicting the decibels (dB) levels before the employee placement on determining the on-site risk. RQ3: Is predicting the decibels (dB) levels before the employee placement on determining the on site risk effective? Ho3: There is no statistically significant relationship between predicting the decibels (dB) levels before the employee placement and effective determination of the on-site risk. Ha3: There is a statistically significant relationship between predicting the decibels (dB) levels before the employee placement and effective determination of the on-site risk. RO4: Establish whether the revised training program is more practicable than the initially adopted initiative. RQ4: Is the revised training program is more practicable than the previously adopted initiative? Ho4: There is no statistically significant proof that the new training program is more feasible than the old program. Ha4: There is statistically significant proof that the new training program is more feasible than the old program. RO5: Determine the blood lead levels variation before and after exposure at the end of the remediation service. RQ5: Do the blood lead levels before and after exposure at the end of the remediation service va ...

1. 11
Sun Coast Remediation: Research Objectives, Research
Questions, and Hypotheses
4
Sun Coast Remediation
Unique R. Simpkins
Southern Columbia University
Course Name Here
Instructor Name
11-2-2021
Research Objectives, Research Questions, and Hypotheses
Based on the information amassed by the former health and
safety director, the organization needs to pursue safety-related
programs or initiatives to ensure employees' health. It is an
appropriate approach to help the firm and the employees
achieve goals and inhibit costs arising from injuries and
illnesses while on duty. The completion of this task will provide
managers with practicable insights on the approach to enhance
safety and protect the firm from losses. This task accounts for
the objectives, questions, and hypotheses of the research based
on the provided statement of the problem.
RO1: Explore the correlation between the size of the Particulate
Matter (PM) and the health of the employee.
RQ1: Is there a correlation between the size of the Particulate

2. Matter (PM) and the health of the employee?
Ho1: There is no statistically significant evidence connecting
the size of the Particulate Matter (PM) and the health of the
employee.
Ha1: There is statistically significant evidence connecting the
size of the Particulate Matter (PM) and the health of the
employee.
RO2: Establish whether safety training is feasible in decreasing
the lost-time hours.
RQ2: Is safety training feasible in decreasing the lost-time
hours?
Ho2: There is no statistically significant evidence linking safety
training and reduction in lost-time hours.
Ha2: There is statistically significant evidence linking safety
training and reduction in lost-time hours.
RO3: Establish the effectiveness of predicting the decibel s (dB)
levels before the employee placement on determining the on-site
risk.
RQ3: Is predicting the decibels (dB) levels before the employee
placement on determining the on site risk effective?
Ho3: There is no statistically significant relationship betw een
predicting the decibels (dB) levels before the employee
placement and effective determination of the on-site risk.
Ha3: There is a statistically significant relationship between
predicting the decibels (dB) levels before the employee
placement and effective determination of the on-site risk.
RO4: Establish whether the revised training program is more
practicable than the initially adopted initiative.
RQ4: Is the revised training program is more practicable than
the previously adopted initiative?
Ho4: There is no statistically significant proof that the new
training program is more feasible than the old program.
Ha4: There is statistically significant proof that the new

3. training program is more feasible than the old program.
RO5: Determine the blood lead levels variation before and after
exposure at the end of the remediation service.
RQ5: Do the blood lead levels before and after exposure at the
end of the remediation service vary?
Ho5: There is no statistically significant evidence showing a
variation in blood lead levels before and after exposure at the
end of the remediation service.
Ha5: There is statistically significant evidence showing a
variation in blood lead levels before and after exposure at the
end of the remediation service.
RO6: Establish whether the four service lines to the
organization's customers differ in return on investment.
RQ6: Do the four service lines to the organization's customers
differ in return on investment?
Ho6: There is no statistically significant proof of the di fference
between the four service lines to the organization's customers in
return on investment.
Ha6: There is statistically significant proof of the difference
between the four service lines to the organization's customers in
return on investment.
References
Creswell, J. W., & Creswell, J. D. (2018). Research design:
Qualitative, quantitative, and mixed methods approaches (5th
ed.). SAGE.

4. White, P. (2017). Developing research questions. Macmillan
International Higher Education.
1. The end of lone-wolf capitalism
For all of our supposed no-nonsense pragmatism, Americans are
romantics, and one of the things we love most is the idea of the
lone-wolf capitalist: the intrepid or brave, solitary genius who
toils in a lab or workshop or office, and suddenly comes up with
some startling invention or new way of doing business. Think
Eli Whitney, Samuel Morse, Thomas Edison, Steve Jobs —
individualists and heroes all.
There is only one problem with this notion. In our global,
networked economy, the lone wolf is rapidly becoming an
anachronism, one that threatens to impede innovation rather
than fostering it.
The roots of entrepreneurial reverence run deep in American
consciousness and history. At least as early as Benjamin
Franklin, who wrote about his rise from meager means to
American gentility, there was a cult of the self-made individual
— especially in contrast to Europe, where success seemed
inherited rather than earned. We have long prided ourselves on
self-reliance; Americans subscribe to a national story that the
country was created through the pluck and guts and brains of
superlative or exceptional individuals. Even our movies
celebrate lone wolves, whether Dirty Harry or Superman.
But while the idea of individual agency may have great appeal,
innovation is increasingly coming from groups, not solitary
heroes. Capitalism as a communal enterprise — dare we call it
collective capitalism? — is the new engine of innovation, in
America and beyond, but it doesn’t seem to square with our
culture.
The new paradigmmight have begun at the dawn of the nuclear
age with the Manhattan Project. A Hollywood version of the

5. U.S. government’s effort to create an atomic weapon during
World War II might have put Albert Einstein or Robert
Oppenheimer in the role of hero, scribbling equations for weeks
at a blackboard before arriving, sweaty and fatigued, at the
eureka moment. The truth? Dozens of physicists worked
collectively, collaboratively and pretty much anonymously. No
eureka moment, no lone hero, no one person challenging fate,
science and bureaucracy.
More recently, the Human Genome Project showed this sort of
collective innovation at work. This effort to map the entire
human DNA chain was launched by the government — an origin
too impersonal to satisfy the entrepreneurial myth we cherish,
and a process too slow for some of the researchers. At the time,
the news media focused on former National Institutes of Health
scientist Craig Venter, who formed a company named Celera to
compete to map the genome. Here was the perfect hero — a lone
individualist.
But the project proved too costly, too intensive, too complex
and — when President Bill Clinton declared that genes could
not be patented — too unprofitable for a lone wolf to do it all
by himself. Venter did soldier on and continued to try to map all
of our human genese, but like the Manhattan Project, the
ultimate success in mapping the human genone was the product
of thousands of scientists in hundreds of institutions, in this
case scattered around the world.
Innovation will always need the people Malcolm Gladwell calls
“tweakers,” such as Steve Jobs, who connect invention to
consumption, and there will never be a dearth or lack of single
entrepreneurs who form companies to market inventions.
Yet, theories about solitude and creativity notwithstanding, the
basic innovative grunt work is now more likely to be done not
by a lone wolf but by a wolf pack; there is simply too much
information and too much complexity for it to be otherwise. We
need a whole lot of brain power because one brain won’t do
anymore.
Already we are seeing how this new innovative collaboration

6. works: in the browser Firefox, which is a product of a
community of thousands of programmers; in the Netflix
algorithm, which is a result of teams of researchers working
together; and in a new automobile company called Local
Motors, which is manufacturing a car based on the ideas of
designers and engineers from around the world who were
brought together by a contest soliciting (asking for) novel or
new approaches to old problems. It boasts on its Web site:
“Now, the crowd drives automotive innovation.” The crowd —
not Henry Ford.
Where we might see both the tenacity of the lone-innovator
myth and its limitations is, oddly enough, in the success of
Facebook. On the surface, the social-networking site would
seem a perfect example of the old entrepreneurial model, with
Mark Zuckerberg (setting aside the pesky question of whether
he really invented the thing) as a sort of modern Alexander
Graham Bell. But when you think about it, while he provided
the critical platform, Zuckerberg created no content whatsoever
and didn’t even hatch—i.e. create--a new way of selling his
service. Everything on Facebook, every last fact, is created by
its users. They are also the ones who “sell” Facebook to other
potential users — their friends. They are the heroes in this
operation, all 800 million of them. Without them, Facebook is
just a blank wall.
There is a name for the theory behind the wolf-pack approach.
It’s called “Reed’s Law,” postulated early in the new
millennium by computer scientist David Reed, and it states that
the utility or power/usefullness of networks increases
exponentially with the number of participants (specifically, 2 to
the nth power), because any single participant can engage with
any number of other participants. Not incidentally, Reed’s Law
built on other theories — an object lesson in its own idea.
Whatever Reed’s Law has to say about social networking, it
also applies to information generally; namely, that the utility of
any information increases exponentially with the number of
individuals accessing it. This points not only to a wiki -culture

7. with billions of collaborators, but to an entire wiki-economy in
which billions of people across the globe collaborate to devise
new relationships to information and inventions.
This new reality doesn’t draw on the American entrepreneurial
myth of singular achievement. It is based instead on something
deeper — our roots as social beings who desire collaboration.
We may like to continue thinking that American individualism
has shaped and will forever shape the modern world, but here is
where cultural self-perceptions and economics can clash or
collide. We have got to overcome our hyperactive sense of
exceptionalism and embrace the more collective, cooperative
and globalized forces shaping the planet. It’s either that or
watch the rest of the world pass us by.
Vocabulary:
pragmatism--character or conduct that emphasizes practicality
(being practical).
anachronism--something or someone that is not in its correct
historical or chronological time, especially a thing or person
that belongs to an earlier time: The sword is an anachronism in
modern warfare.
fostering—helping to grow or develop
gentility—the status of belonging to the highest parts of society
(in terms of wealth and arrogance)
Manhattan Project--the unofficial designation or name for the
U.S. War Department's secret program, organized in 1942, to
explore produce an atomic bomb: initial research was conducted
at Columbia University in Manhattan.
Running head: INSERT TITLE HERE 1

8. INSERT TITLE HERE 17
Insert Title Here
Insert Your Name Here
Insert University Here
Sun Coast Remediation Course Project Guidance
Background
To help make a connection between business research and its
use in the real world, this course will use an iterative course
project. Throughout the term, you will serve as the health and
safety director for Sun Coast Remediation (Sun Coast).
Sun Coast provides remediation services to business and
governmental organizations. Most of their contracts involve
working within contamination sites where they remove toxic
substances from soil and water. In addition to the toxicity of the
air, water, and soil their employees come into contact with, the
work environment is physically demanding and potentially
contributory to injuries involving musculoskeletal systems,
vision, and hearing. Sun Coast genuinely cares about the health,
safety, and well-being of their 5,500 employees, but they are
also concerned about worker compensation costs and potential
long-term litigation from injuries and illness related to
employment.

9. Health and Safety Director Task
Sun Coast hired you last month to replace the previous health
and safety director, who left to pursue other opportunities. This
is a critical position within the company because there are many
health and safety-related issues due to the nature of the work.
The former health and safety director was in the midst of
analyzing these issues through the implementation of a research
project when she left the organization.
Throughout the term, you will use your knowledge of research
methods to bring the research project to fruition. You will
conduct a literature review, develop research questions and
hypotheses, create the research design, test data, interpret data,
and present the findings. Each unit will accomplish one of these
tasks. It has already been decided that the business problems
will be best addressed using a quantitative research
methodology. You will not collect any data for this project. The
former health and safety director had already collected the data,
which is provided for you in an Excel spreadsheet.
Statistical Tools
You will conduct the data analysis using Microsoft Excel
Toolpak. View these links for information:
https://support.office.com/en-us/article/load-the-analysis-
toolpak-in-excel-6a63e598-cd6d-42e3-9317-6b40ba1a66b4 and
https://www.excel-easy.com/data-analysis/analysis-toolpak.html
Sun Coast Remediation Course Project Sections
Since this is a quantitative research study, there are specific
steps that should be followed. The following is a template that
will help you develop your project. (It is also provided as a
template in Unit VII.) Use this information to guide your

10. completion of the course project.
Table of Contents
Include the table of contents here. There is a tool for creating a
table of contents in the References tab of the Microsoft Word
tool bar at the top of the screen. Remember to delete this text
and the instructions from the previous page before you begin.
Executive Summary
The executive summary will go here. The paragraphs are not
indented, and it should be formatted like an abstract. The
executive summary should be composed after the project is
complete. It will be the final step in the project. Delete this text
before you begin.
Sun Coast Remediation Course Project
Introduction
Note: The following introduction should remain in the research
project unchanged. Delete this note before you begin.
Senior leadership at Sun Coast has identified several areas for
concern that they believe could be solved using business
research methods. The previous director was tasked with
conducting research to help provide information to make
decisions about these issues. Although data were collected, the
project was never completed. Senior leadership is interested in
seeing the project through to fruition. The following is the
completion of that project and includes the statement of the
problems, literature review, research objectives, research
questions and hypotheses, research methodology, design, and
methods, data analysis, findings, and recommendations.
Statement of the Problems
Note: The following statement of the problems should remain in
the research project unchanged. Delete this note before you
begin.
Six business problems were identified:
Particulate Matter (PM)

11. There is a concern that job-site particle pollution is adversely
impacting employee health. Although respirators are required in
certain environments, PM varies in size depending on the
project and job site. PM that is between 10 and 2.5 microns can
float in the air for minutes to hours (e.g., asbestos, mold spores,
pollen, cement dust, fly ash), while PM that is less than 2.5
microns can float in the air for hours to weeks (e.g. bacteria,
viruses, oil smoke, smog, soot). Due to the smaller size of PM
that is less than 2.5 microns, it is potentially more harmful than
PM that is between 10 and 2.5 since the conditions are more
suitable for inhalation. PM that is less than 2.5 is also able to be
inhaled into the deeper regions of the lungs, potentially causing
more deleterious health effects. It would be helpful to
understand if there is a relationship between PM size and
employee health. PM air quality data have been collected from
103 job sites, which is recorded in microns. Data are also
available for average annual sick days per employee per job-
site.
Safety Training Effectiveness
Health and safety training is conducted for each new contract
that is awarded to Sun Coast. Data for training expenditures and
lost-time hours were collected from 223 contracts. It would be
valuable to know if training has been successful in reducing
lost-time hours and, if so, how to predict lost-time hours from
training expenditures.
Sound-Level Exposure
Sun Coast’s contracts generally involve work in noisy
environments due to a variety of heavy equipment being used
for both remediation and the clients’ ongoing operations on the
job sites. Standard ear-plugs are adequate to protect employee
hearing if the decibel levels are less than 120 decibels (dB). For
environments with noise levels exceeding 120 dB, more
advanced and expensive hearing protection is required, such as
earmuffs. Historical data have been collected from 1,503
contracts for several variables that are believed to contribute to
excessive dB levels. It would be important if these data could

12. be used to predict the dB levels of work environments before
placing employees on-site for future contracts. This would help
the safety department plan for procurement of appropriate ear
protection for employees.
New Employee Training
All new Sun Coast employees participate in general health and
safety training. The training program was revamped and
implemented six months ago. Upon completion of the training
programs, the employees are tested on their knowledge. Test
data are available for two groups: Group A employees who
participated in the prior training program and Group B
employees who participated in the revised training program. It
is necessary to know if the revised training program is more
effective than the prior training program.
Lead Exposure
Employees working on job sites to remediate lead must be
monitored. Lead levels in blood are measured as micrograms of
lead per deciliter of blood (μg/dL). A baseline blood test is
taken pre-exposure and postexposure at the conclusion of the
remediation. Data are available for 49 employees who recently
concluded a 2-year lead remediation project. It is necessary to
determine if blood lead levels have increased.
Return on Investment
Sun Coast offers four lines of service to their customers,
including air monitoring, soil remediation, water reclamation,
and health and safety training. Sun Coast would like to know if
each line of service offers the same return on investment.
Return on investment data are available for air monitoring, soil
remediation, water reclamation, and health and safety training
projects. If return on investment is not the same for all lines of
service, it would be helpful to know where differences exist.
Literature Review
After providing a brief introduction to this section, students
should include the literature review information here. Important
Note: Students should refer to the information presented in the
Unit I Study Guide and the Unit I Syllabus instructions to

13. complete this section of the project. Delete this before you
begin.
Research Objectives
After providing a brief introduction to this section, students
should include research objectives here. Students should
compose short, direct statements about the objectives of the
study. Research objectives should relate to the problems that
have been identified above, and there should be one objective
for each problem as shown in the example below. Important
Note: Students should refer to the information presented in the
Unit II Syllabus instructions to complete this section of the
project. Delete this before you begin.
Example:
RO1: Determine if a person’s height is related to weight.
RO2:
RO3:
RO4:
RO5:
RO6:
Research Questions and Hypotheses
After providing a brief introduction to this section, students
should state the research questions and hypotheses. Each
research objective should have a corresponding research
question and a null and alternative hypothesis as shown in the
example below. In total, there should be six research questions
and twelve hypotheses. Important Note: Students should refer to
the information presented in the Unit II Study Guide and the
Unit II Syllabus instructions to complete this section of the
project. Delete this before you begin.
Example:
RQ1: Is there a relationship between height and weight?
H01: There is no statistically significant relationship between
height and weight.
HA1: There is a statistically significant relationship between
height and weight.

14. RQ2:
H02:
HA2:
RQ3:
H03:
HA3:
RQ4:
H04:
HA4:
RQ5:
H05:
HA5:
RQ6:
H06:
HA6:
Research Methodology, Design, and Methods
After providing a brief introduction to this section, students
should detail the research design they have selected and why it
is an appropriate research approach for addressing the business
problems. Use the following subheadings to include all required
information. Important Note: Students should refer to the
information presented in the Unit III Study Guide and the Unit
III Syllabus instructions to complete this section of the project.
Delete this before you begin.
Research Methodology
Explain the research methodology chosen for this research
project and provide rationale for why it is appropriate given the
problems.
Research Design
Students should explain whether the research design is
exploratory, causal, or descriptive. Provide rationale for the
choice.

15. Research Methods
Students should describe the research methods used for this
research study based on the research methodology, research
design, and research questions, and provide a rationale as to
why they were chosen. They might include a combination of
experimentation, descriptive statistics, correlation, and causal -
comparative methods.
Data Collection Methods
Students should specify how the data were most likely collected
to test the hypotheses. Data collection methods include, but are
not limited to, survey, observation, and records analysis.
Sampling Design
Students should briefly describe the type of sampling design
that was most likely used for the data that were collected.
Choices include, but are not limited to, random sample,
convenience sample, etc. Explain your rationale for your
sampling design selection(s).
Data Analysis Procedures
Students should specify the statistical procedures used to test
each set of hypotheses from among correlation, regression, t
test, and ANOVA. They should explain why each procedure was
the most appropriate choice.
Example:
Correlation is the preferred procedure to use to test the RQ1
hypotheses since the interest is whether a relationship exists
between an independent variable (IV) and dependent variable
(DV). Correlation will indicate if there is a relationship between
height (IV) and weight (DV), the strength of the relationship,
and the direction of the relationship.
Data Analysis: Descriptive Statistics and Assumption Testing
After providing a brief introduction to this section, students
should provide the Excel Toolpak results of their descriptive
analyses. Frequency tables, histograms, and descriptive
statistics tables should be cut and pasted from Excel directly
into the final project document. Important Note: Students
should refer to the information presented in the Unit IV Study

16. Guide and the Unit IV Syllabus instructions to complete this
section of the project. Delete this before you begin.
Correlation: Descriptive Statistics and Assumption Testing
Students should include this information here. Include
frequency table, histogram, and descriptive statistics table.
Evaluate and discuss the descriptive statistics and make an
explicit statement about whether the assumptions for parametric
statistical testing were met or not met. Delete these statements
before you begin.
Simple Regression: Descriptive Statistics and Assumption
Testing
Students should include this information here. Include
frequency table, histogram, and descriptive statistics table.
Evaluate and discuss the descriptive statistics, and make an
explicit statement about whether the assumptions for parametric
statistical testing were met or not met. Delete these statements
before you begin.
Multiple Regression: Descriptive Statistics and Assumption
Testing
Students should include this information here. Include
frequency table, histogram, and descriptive statistics table.
Evaluate and discuss the descriptive statistics and make an
explicit statement about whether the assumptions for parametric
statistical testing were met or not met. Delete these statements
before you begin.
Independent Samples t Test: Descriptive Statistics and
Assumption Testing
Students should include this information here. Include
frequency table, histogram, and descriptive statistics table.
Evaluate and discuss the descriptive statistics, and make an
explicit statement about whether the assumptions for parametric
statistical testing were met or not met. Delete these statements
before you begin.
Dependent Samples (Paired-Samples) t Test: Descriptive
Statistics and Assumption Testing
Students should include this information here. Include

17. frequency table, histogram, and descriptive statistics table.
Evaluate and discuss the descriptive statistics, and make an
explicit statement about whether the assumptions for parametric
statistical testing were met or not met. Delete these statements
before you begin.
ANOVA: Descriptive Statistics and Assumption Testing
Students should include this information here. Include
frequency table, histogram, and descriptive statistics table.
Evaluate and discuss the descriptive statistics, and make an
explicit statement about whether the assumptions for parametric
statistical testing were met or not met. Delete these statements
before you begin
Data Analysis: Hypothesis Testing
After providing a brief introduction to this section, students
should provide the Excel Toolpak results of their hypothesis
testing. The statistical output tables should be cut and pasted
from Excel directly into the final project document. For the
regression hypotheses, the students should display and discuss
the predictive regression equations. Important Note: Students
should refer to the information presented in the Units V and VI
Study Guides and the Units V and VI Syllabus instructions to
complete this section of the project. Delete this before you
begin.
Correlation: Hypothesis Testing
Students should include this information here. Restate the null
and alternative hypotheses, cut and paste the statistical output
from Excel Toolpak, discuss the p-value in relation to alpha and
explicitly accept or reject the null and alternative hypotheses.
Delete these statements before you begin.
Simple Regression: Hypothesis Testing
Students should include this information here. Restate the
null and alternative hypotheses, cut and paste the statistical
output from Excel Toolpak, and interpret and explain the simple
regression analysis results below the Excel output. Your
explanation should include: multiple R, R square, alpha level,
ANOVA F value, accept or reject the null and alternative

18. hypotheses for the model, statistical significance of the x
variable coefficient, and the regression model as an equation
with explanation. Delete these statements before you begin.
Multiple Regression: Hypothesis Testing
Students should include this information here. Restate the null
and alternative hypotheses, cut and paste the statistical output
from Excel Toolpak, and interpret and explain the simple
regression analysis results below the Excel output. Your
explanation should include: multiple R, R square, alpha level,
ANOVA F value, accept or reject the null and alternative
hypotheses for the model, statistical significance of the x
variable coefficients, and the regression model as an equation
with explanation.
Independent Samples t Test: Hypothesis Testing
Students should include this information here. Restate the null
and alternative hypotheses, cut and paste the statistical output
from Excel Toolpak, discuss the p-value in relation to alpha and
explicitly accept or reject the null and alternative hypotheses.
Delete these statements before you begin.
Dependent Samples (Paired Samples) t Test: Hypothesis Testing
Students should include this information here. Restate the null
and alternative hypotheses, cut and paste the statistical output
from Excel Toolpak, discuss the p-value in relation to alpha and
explicitly accept or reject the null and alternative hypotheses.
Delete these statements before you begin.
ANOVA: Hypothesis Testing
Students should include this information here. Restate the null
and alternative hypotheses, cut and paste the statistical output
from Excel Toolpak, discuss the p-value in relation to alpha and
explicitly accept or reject the null and alternative hypotheses.
Delete these statements before you begin.
Findings
After providing a brief introduction to this section,
students should discuss the findings in the context of Sun
Coast’s problems and the associated research objectives and
research questions. Important Note: Students should refer to the

19. information presented in the Unit VII Study Guide and the Unit
VII Syllabus instructions to complete this section of the project.
Restate each research objective, and discuss them in the context
of your hypothesis testing results. The following are some
things to consider. What answers did the analysis provide to
your research questions? What do those answers tell you? What
are the implications of those answers? Delete these statements
before you begin.
Example:
RO1: Determine if a person’s height is related to weight.
The results of the statistical testing showed that a person’s
height is related to their weight. It is a relatively strong and
positive relationship between height and weight. We would,
therefore, expect to see in our population taller people having a
greater weight relative to those of shorter people. This
determination suggests restrictions on industrial equipment
should be stated in maximum pounds allowed rather than
maximum number of people allowed.
RO2:
RO3:
RO4:
RO5:
RO6:
Recommendations
After providing a brief introduction to this section, students
should include recommendations here in paragraph form. This
section should be your professional thoughts based upon the
results of the hypothesis testing. You are the researcher, and
Sun Coast's leadership team is relying on you to make evidence-
based recommendations. Delete these statements before you
begin.
References
Include references here using hanging indentations, and delete
these statements and example reference.
Creswell, J. W., & Creswell, J. D. (2018). Research design:

20. Qualitative, quantitative, and mixed methods approaches (5th
ed.). Thousand Oaks, CA: Sage.
11
2
Insert Title Here
Insert Your Name Here
Insert University Here
Course Name Here
Instructor Name
Date
Research Objectives, Research Questions, and Hypotheses
After providing a brief introduction to this section,
students should include research objectives, research questions,
and hypotheses here. There should be 1 research objective, 1
research question, and 2 hypotheses (both a null and alternative)
for each of the 6 problems described in the Statement of
Problems section of the Course Project Guidance document.
Students should compose 6 short, direct, statements about
the objectives of the study. Research objectives should relate
directly to the 6 problems that have been described in the
Statement of Problems and there should be 1 objective for each
problem.
Each research objective should also have a corresponding
research question and a null and alternative hypothesis as shown
in the example below. Research questions and hypothes es
should specifically state the variables being measured.
In total, there should be 6 research objectives, 6 research

21. questions, and 12 hypotheses as shown below in the template.
Important Note: Students should refer to the information
presented in the Unit II syllabus instructions to complete this
section of the project. Delete instructions and examples
highlighted in yellow before submitting this assignment.
Example:
RO1: Determine if a person’s height is related to weight.
RQ1: Is there a relationship between height and weight?
Ho1: There is no statistically significant relationship between
height and weight.
Ha1: There is a statistically significant relationship between
height and weight.
RO2:
RQ2:
Ho2:
Ha2:
RO3:
RQ3:
Ho3:
Ha3:
RO4:
RQ4:
Ho4:
Ha4:
RO5:
RQ5:
Ho5:
Ha5:
RO6:
RQ6:
Ho6:

22. Ha6:
References
Include references here using hanging indentations.
Creswell, J. W., & Creswell, J. D. (2018). Research design:
Qualitative, quantitative, and mixed methods approaches (5th
ed.). SAGE.
1
2
Insert Title Here
Insert Your Name Here
Insert University Here
Course Name Here
Instructor Name
Date
Data Analysis: Hypothesis Testing
Use the Sun Coast Remediation data set to conduct an
independent samples t test, dependent samples (paired sampl es)
t test, and ANOVA using the independent samples tab, paired
samples tab, and ANOVA tab in the Sun Coast data file. The
statistical output tables should be cut and pasted from Excel
directly into the final project document. Delete instructions and
examples highlighted in yellow before submitting this
assignment.
Independent Samples t Test: Hypothesis Testing
Restate the hypotheses from Unit II here.

23. Ho4:
Ha4:
Provide data output results from Excel Toolpak here.
Interpret and explain the independent samples t test results
below the Excel output here. Include alpha level, p value, and
accept or reject the null and alternative hypotheses.
Example:
Ho4: There is no statistically significant difference in mean
values for the DV between Group A(IV1) and Group B (IV2).
Ha4: There is a statistically significant difference in mean
values for the DV between Group A (IV1) and Group B (IV2).
The results indicate that the mean values are lower for
Group A; however, the results also indicate a p value of .37627
> .05. Therefore, the null hypothesis is accepted that there is no
statistically significant difference in mean values of the DV
between Group A (IV1) and Group B (IV2).
Dependent Samples (Paired Samples) t Test: Hypothesis Testing
Restate the hypotheses from Unit II here.
Ho5:
Ha5:
Provide data output results from Excel Toolpak here.
Interpret and explain the dependent t test results below the
Excel output here. Include alpha level, p value, and accept or
reject the null and alternative hypotheses.
ANOVA: Hypothesis Testing
Restate the hypotheses from Unit II here.
Ho6:
Ha6:
Provide data output results from Excel Toolpak here.
Interpret and explain the ANOVA results below the Excel
output here. Include alpha level, p value, and accept or reject
the null and alternative hypotheses.
References
Include references here using hanging indentations.

24. Creswell, J. W., & Creswell, J. D. (2018). Research design:
Qualitative, quantitative, and mixed methods approaches (5th
ed.). SAGE.