Week 5 Project PHE4120 Health Disparities And Minority Health Best College Essay Help

 

Week 5 Final ProjectAssignment Due March 21 at 11:59 PMNCF:
This final project assignment is associated with the NCF (non-completion failure) grade. Failure to complete this assignment will result in the issuance of a grade of NCF if the course average would result in a failing grade in the course. Students should contact their Academic Counselor or Program Director if they have any questions regarding the NCF grade and its implications.
Supporting Lectures:
Refer the following lecture:

Steps to Reduce Health Disparities

Identifying Health Disparities
Using the South University Online Library or the Internet, research and read about a specific health disparity of interest to you. This can be based on gender, age, race, ethnicity, sexual orientation, gender identity, etc.
Based on your research and data gathered, create a report in a 8 to 10 page paper that addresses the following:

What is the background of the disparity chosen?

Who does this disparity impact? 

What are the determinants of this disparity?

What is the impact of this disparity?

Is there an intersection of multiple concerns related to race/ethnicity, gender, and sexuality related to this issue?

How and where would one seek to intervene to address this disparity in the context of the social ecological model?

How does this disparity affect the health of the population on a larger scale?

How does your race/ethnicity, gender, sexual orientation, or SES impact your ability to work within the community affected by this disparity?

Submission Details:

 Submit your document SU_PHE4120_W5_Project_LastName_FirstInitial.doc.

 Submit your document to the Submissions Area by the due date assigned.

 Cite any sources in APA format.

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uploaded is a project and a close out … needing a lessons learned use the template provided. no sources custom essay help

uploaded is a project and a close out … needing a lessons learned use the template provided.
no sources needed
the first two pages are a copy and paste… copy and paste from the header or title page and copy and paste from the template the table of contents on page two.. page three starts the lessons learned.

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Read the article “Key Trends in Workforce Management and New Challenges for HR.” located in the Business Source Complete writing essay help: writing essay help

Read the article “Key Trends in Workforce Management and New Challenges for HR.” located in the Business Source Complete database of the CSU Online Library by clicking the link below:
Moschetto, M. (2014, Winter). Key trends in workforce management and new challenges for HR. Employment Relations Today, 40(4), 7–13. https://libraryresources.columbiasouthern.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true

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EXPLAINING WATER MAIN INTEGRITY: THE CITY OF MAKEFIELD BACKGROUND As an elected executive (mayor) in the City of Makefield, your major concern is the quality of infrastructure in the municipality. college essay help near me

  Makefield is an old industrial city with aging infrastructure.   While campaigning you observed that city residents, particularly those who live in the western part of the city, consistently expressed concerns about loss of water pressure and water main leaks in their neighborhoods as opposed to resident in the eastern part of the city. 
You decide to embark on an explanatory analysis of water main integrity in the eastern and western parts of the city (the city has two main districts of water distribution—one in the eastern section of the city and the other in the western part of the city). 
THE WATER MAIN PROBLEM: WHAT ARE WE MEASURING?  
Your management problem is the integrity of water mains in the city—How sound is the construction of the water mains given their age (much of the water main infrastructure is over 70 years old)? Using 311 data, your staff uses resident complaints of water leaks and breaks measured at the nominal level where 1=a break or leak and 0=no break or leak.  This information will be analyzed by water district of the city, where 1=west district and 2=east district. In an effort to confirm if water district has an impact on the frequency of water breaks and leaks, your staff decides to examine the impact of district on the frequency of water main complaints by season. The goal here is to ascertain if season exasperates water breaks or leaks for a particular district. 
DECISION CONSIDERATIONS 
Your facilitates manager has recommended the development of a capital improvement plan for the city’s water distribution system.  However, this initiative has been put on hold since a data analysis is lacking. The facilitates manager would also like some direction on where to start if a capital improvement plan is to be pursued. 
I.               The Issue/Problem and Hypothesis
Hiring or hiring status of patrol officers is the management problem. It is hypothesized that black applicants will be over represented in selections for positions.
II.             Measurement of the Problem and Independent Variables
The dependent variable, hiring status, which is measured at the nominal level, where 1=hired and 2=not hired. The independent variable is race of the applicant, which is measured at the nominal level where 1=black and 2=non-­black. 
A control variable, residency of applicants, was used to see if the relationship between race and hiring status holds true, based on where applicants live. The control variable, residency of applicants, is measured at the nominal level, where 1=lives in Metro City and=resides outside of the city.
III.            Quantitative Approach Used
A Contingency Table Analysis (CTA) was used to test above hypothesis by determining if a statistically significant relationship existed between race and hire. This quantitative technique was used because the dependent variable (hiring status), the independent variable (race of applicant) and the control variable (residency) are all measured at the nominal level. 
IV.           Analysis of the Data
Table 1 presents a contingency table that assesses the influence of race of applicant on hiring for law enforcement patrolman positions.  
TABLE 1: ASSESSING THE IMPACT OF RACE ON POLICE HIRING
TABLE 1: ASSESSING THE IMPACT OF RACE ON POLICE HIRING
Chi Square; p=.03
Table 1 supports the above hypothesis in that it was expected that 22 black applicants would be hired yet the actual number of black applicants selected was a 28; 6 more applicants than expected. The Chi Square test of statistical significance suggests that we can be 97 percent confident that the difference between the expected and actual number of black applicants hired is attributed to race. 
Table 2 elaborates on Table 1 by examining the impact of race on hiring by municipal residency of applicants for patrolmen positions.  Since residency of an applicant could have an influence on hiring, a decision was made to statistically control for this variable to see if race continues to yield a systemic overrepresentation of black applicants in available patrolmen positions.   
To assess if the original hypothesis–that race impacts hiring–is statistically significant while considering residency of applicants, the expected and actual number of hires among black applicants are compared in Table 2. For example, it was expected that for applicants residing in the city, 12 black applicants would be hired and in actuality 16 black applicants were hired. Indeed, while there is over representation of black applicants who reside in city, the Chi Square test of statistical significance suggests that we can be 94.3 percent confident that the difference between the expected and actual number of black applicants hired is attributed to race for those applicants who live in the city.  Therefore, the impact of race on the difference between the expected and actual number of hires is considered random for applicants living in the city. 
TABLE 2: ASSESSING THE IMPACT OF RACE ON POLICE HIRINGBY RESIDENCY
Live in City, Chi Square; p=.057
Live Outside the City; p=. 302
I.               Decision Outcomes and Inquiry of Staff
The findings indicate that race does not have a systematic impact on hiring and the overrepresentation of hires of black applicants.  Instead, residency of the applicant has more of an influence on hiring. 
One question to ask Human Resources staff is: Does the city have a residency rule for hiring? If so, this policy can be influencing the hiring outcome.  Nonetheless, race is not a factor and the city should proceed with the hires.  

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Purpose: The purpose of this assignment is to create a chart of teacher-designed strategies based on specific objectives and Essay best essay help: best essay help

Purpose: The purpose of this assignment is to create a chart of teacher-designed strategies based on specific objectives and for learners of diverse ability levels.

Directions:

Select one of the BEST standards (K-3).
B.E.S.T Standards Reading/Language Arts and Mathematics https://www.cpalms.org/Standards/BEST_Standards.aspx
Write an objective based on the standard. (The objective must include ABCD)
Develop two learning activities (on-grade level)
Develop two corrective activities (remediation)
Develop two enrichment activities (above grade level). Make sure to use Webb’s Depths of Knowledge for this assignment pg. 230.
You will have a total of six activities, two for each category.
Save your work in a word document.

***You may use the following template to complete your assignment.

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EXPLAINING WATER MAIN INTEGRITY: THE CITY OF MAKEFIELD BACKGROUND As an elected executive (mayor) in the City of Makefield, your major concern is the quality of infrastructure in the municipality. EXP college essay help online: college essay help online

EXPLAINING WATER MAIN INTEGRITY: THE CITY OF MAKEFIELD
BACKGROUND
As an elected executive (mayor) in the City of Makefield, your major concern is the quality of infrastructure in the municipality.  Makefield is an old industrial city with aging infrastructure.   While campaigning you observed that city residents, particularly those who live in the western part of the city, consistently expressed concerns about loss of water pressure and water main leaks in their neighborhoods as opposed to resident in the eastern part of the city. 
You decide to embark on an explanatory analysis of water main integrity in the eastern and western parts of the city (the city has two main districts of water distribution—one in the eastern section of the city and the other in the western part of the city). 
THE WATER MAIN PROBLEM: WHAT ARE WE MEASURING?  
Your management problem is the integrity of water mains in the city—How sound is the construction of the water mains given their age (much of the water main infrastructure is over 70 years old)? Using 311 data, your staff uses resident complaints of water leaks and breaks measured at the nominal level where 1=a break or leak and 0=no break or leak.  This information will be analyzed by water district of the city, where 1=west district and 2=east district. In an effort to confirm if water district has an impact on the frequency of water breaks and leaks, your staff decides to examine the impact of district on the frequency of water main complaints by season. The goal here is to ascertain if season exasperates water breaks or leaks for a particular district. 
DECISION CONSIDERATIONS 
Your facilitates manager has recommended the development of a capital improvement plan for the city’s water distribution system.  However, this initiative has been put on hold since a data analysis is lacking. The facilitates manager would also like some direction on where to start if a capital improvement plan is to be pursued. 
I.               The Issue/Problem and Hypothesis
Hiring or hiring status of patrol officers is the management problem. It is hypothesized that black applicants will be over represented in selections for positions.
II.             Measurement of the Problem and Independent Variables
The dependent variable, hiring status, which is measured at the nominal level, where 1=hired and 2=not hired. The independent variable is race of the applicant, which is measured at the nominal level where 1=black and 2=non-­black. 
A control variable, residency of applicants, was used to see if the relationship between race and hiring status holds true, based on where applicants live. The control variable, residency of applicants, is measured at the nominal level, where 1=lives in Metro City and=resides outside of the city.
III.            Quantitative Approach Used
A Contingency Table Analysis (CTA) was used to test above hypothesis by determining if a statistically significant relationship existed between race and hire. This quantitative technique was used because the dependent variable (hiring status), the independent variable (race of applicant) and the control variable (residency) are all measured at the nominal level. 
IV.           Analysis of the Data
Table 1 presents a contingency table that assesses the influence of race of applicant on hiring for law enforcement patrolman positions.  
TABLE 1: ASSESSING THE IMPACT OF RACE ON POLICE HIRING
TABLE 1: ASSESSING THE IMPACT OF RACE ON POLICE HIRING
Chi Square; p=.03
Table 1 supports the above hypothesis in that it was expected that 22 black applicants would be hired yet the actual number of black applicants selected was a 28; 6 more applicants than expected. The Chi Square test of statistical significance suggests that we can be 97 percent confident that the difference between the expected and actual number of black applicants hired is attributed to race. 
Table 2 elaborates on Table 1 by examining the impact of race on hiring by municipal residency of applicants for patrolmen positions.  Since residency of an applicant could have an influence on hiring, a decision was made to statistically control for this variable to see if race continues to yield a systemic overrepresentation of black applicants in available patrolmen positions.   
To assess if the original hypothesis–that race impacts hiring–is statistically significant while considering residency of applicants, the expected and actual number of hires among black applicants are compared in Table 2. For example, it was expected that for applicants residing in the city, 12 black applicants would be hired and in actuality 16 black applicants were hired. Indeed, while there is over representation of black applicants who reside in city, the Chi Square test of statistical significance suggests that we can be 94.3 percent confident that the difference between the expected and actual number of black applicants hired is attributed to race for those applicants who live in the city.  Therefore, the impact of race on the difference between the expected and actual number of hires is considered random for applicants living in the city. 
TABLE 2: ASSESSING THE IMPACT OF RACE ON POLICE HIRINGBY RESIDENCY
Live in City, Chi Square; p=.057
Live Outside the City; p=. 302
I.               Decision Outcomes and Inquiry of Staff
The findings indicate that race does not have a systematic impact on hiring and the overrepresentation of hires of black applicants.  Instead, residency of the applicant has more of an influence on hiring. 
One question to ask Human Resources staff is: Does the city have a residency rule for hiring? If so, this policy can be influencing the hiring outcome.  Nonetheless, race is not a factor and the city should proceed with the hires. 

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EXPLAINING WATER MAIN INTEGRITY: THE CITY OF MAKEFIELD BACKGROUND As an elected executive (mayor) in the City of Makefield, your major concern is the quality of infrastructure in the municipality. EXP best college essay help

EXPLAINING WATER MAIN INTEGRITY: THE CITY OF MAKEFIELD
BACKGROUND
As an elected executive (mayor) in the City of Makefield, your major concern is the quality of infrastructure in the municipality.  Makefield is an old industrial city with aging infrastructure.   While campaigning you observed that city residents, particularly those who live in the western part of the city, consistently expressed concerns about loss of water pressure and water main leaks in their neighborhoods as opposed to resident in the eastern part of the city. 
You decide to embark on an explanatory analysis of water main integrity in the eastern and western parts of the city (the city has two main districts of water distribution—one in the eastern section of the city and the other in the western part of the city). 
THE WATER MAIN PROBLEM: WHAT ARE WE MEASURING?  
Your management problem is the integrity of water mains in the city—How sound is the construction of the water mains given their age (much of the water main infrastructure is over 70 years old)? Using 311 data, your staff uses resident complaints of water leaks and breaks measured at the nominal level where 1=a break or leak and 0=no break or leak.  This information will be analyzed by water district of the city, where 1=west district and 2=east district. In an effort to confirm if water district has an impact on the frequency of water breaks and leaks, your staff decides to examine the impact of district on the frequency of water main complaints by season. The goal here is to ascertain if season exasperates water breaks or leaks for a particular district. 
DECISION CONSIDERATIONS 
Your facilitates manager has recommended the development of a capital improvement plan for the city’s water distribution system.  However, this initiative has been put on hold since a data analysis is lacking. The facilitates manager would also like some direction on where to start if a capital improvement plan is to be pursued. 
I.               The Issue/Problem and Hypothesis
Hiring or hiring status of patrol officers is the management problem. It is hypothesized that black applicants will be over represented in selections for positions.
II.             Measurement of the Problem and Independent Variables
The dependent variable, hiring status, which is measured at the nominal level, where 1=hired and 2=not hired. The independent variable is race of the applicant, which is measured at the nominal level where 1=black and 2=non-­black. 
A control variable, residency of applicants, was used to see if the relationship between race and hiring status holds true, based on where applicants live. The control variable, residency of applicants, is measured at the nominal level, where 1=lives in Metro City and=resides outside of the city.
III.            Quantitative Approach Used
A Contingency Table Analysis (CTA) was used to test above hypothesis by determining if a statistically significant relationship existed between race and hire. This quantitative technique was used because the dependent variable (hiring status), the independent variable (race of applicant) and the control variable (residency) are all measured at the nominal level. 
IV.           Analysis of the Data
Table 1 presents a contingency table that assesses the influence of race of applicant on hiring for law enforcement patrolman positions.  
TABLE 1: ASSESSING THE IMPACT OF RACE ON POLICE HIRING
TABLE 1: ASSESSING THE IMPACT OF RACE ON POLICE HIRING
Chi Square; p=.03
Table 1 supports the above hypothesis in that it was expected that 22 black applicants would be hired yet the actual number of black applicants selected was a 28; 6 more applicants than expected. The Chi Square test of statistical significance suggests that we can be 97 percent confident that the difference between the expected and actual number of black applicants hired is attributed to race. 
Table 2 elaborates on Table 1 by examining the impact of race on hiring by municipal residency of applicants for patrolmen positions.  Since residency of an applicant could have an influence on hiring, a decision was made to statistically control for this variable to see if race continues to yield a systemic overrepresentation of black applicants in available patrolmen positions.   
To assess if the original hypothesis–that race impacts hiring–is statistically significant while considering residency of applicants, the expected and actual number of hires among black applicants are compared in Table 2. For example, it was expected that for applicants residing in the city, 12 black applicants would be hired and in actuality 16 black applicants were hired. Indeed, while there is over representation of black applicants who reside in city, the Chi Square test of statistical significance suggests that we can be 94.3 percent confident that the difference between the expected and actual number of black applicants hired is attributed to race for those applicants who live in the city.  Therefore, the impact of race on the difference between the expected and actual number of hires is considered random for applicants living in the city. 
TABLE 2: ASSESSING THE IMPACT OF RACE ON POLICE HIRINGBY RESIDENCY
Live in City, Chi Square; p=.057
Live Outside the City; p=. 302
I.               Decision Outcomes and Inquiry of Staff
The findings indicate that race does not have a systematic impact on hiring and the overrepresentation of hires of black applicants.  Instead, residency of the applicant has more of an influence on hiring. 
One question to ask Human Resources staff is: Does the city have a residency rule for hiring? If so, this policy can be influencing the hiring outcome.  Nonetheless, race is not a factor and the city should proceed with the hires. 

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Assignment: Identify the main purpose and mission of a PMO and explain the main challenges and obstacles in implementing college essay help near me: college essay help near me

Assignment:
Identify the main purpose and mission of a PMO and explain the main challenges and obstacles in implementing a PMO. (“AtekPC Project Management Office,” Harvard Business Review)
(Please minimize using direct quote from references as professor does not like it)

My notes:
Main purpose

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EXPLAINING WATER MAIN INTEGRITY: THE CITY OF MAKEFIELD BACKGROUND As an elected executive (mayor) in the City of Makefield, your major concern is the quality of infrastructure in the municipality. EXP college essay help

EXPLAINING WATER MAIN INTEGRITY: THE CITY OF MAKEFIELD
BACKGROUND
As an elected executive (mayor) in the City of Makefield, your major concern is the quality of infrastructure in the municipality.  Makefield is an old industrial city with aging infrastructure.   While campaigning you observed that city residents, particularly those who live in the western part of the city, consistently expressed concerns about loss of water pressure and water main leaks in their neighborhoods as opposed to resident in the eastern part of the city. 
You decide to embark on an explanatory analysis of water main integrity in the eastern and western parts of the city (the city has two main districts of water distribution—one in the eastern section of the city and the other in the western part of the city). 
THE WATER MAIN PROBLEM: WHAT ARE WE MEASURING?  
Your management problem is the integrity of water mains in the city—How sound is the construction of the water mains given their age (much of the water main infrastructure is over 70 years old)? Using 311 data, your staff uses resident complaints of water leaks and breaks measured at the nominal level where 1=a break or leak and 0=no break or leak.  This information will be analyzed by water district of the city, where 1=west district and 2=east district. In an effort to confirm if water district has an impact on the frequency of water breaks and leaks, your staff decides to examine the impact of district on the frequency of water main complaints by season. The goal here is to ascertain if season exasperates water breaks or leaks for a particular district. 
DECISION CONSIDERATIONS 
Your facilitates manager has recommended the development of a capital improvement plan for the city’s water distribution system.  However, this initiative has been put on hold since a data analysis is lacking. The facilitates manager would also like some direction on where to start if a capital improvement plan is to be pursued. 
I.               The Issue/Problem and Hypothesis
Hiring or hiring status of patrol officers is the management problem. It is hypothesized that black applicants will be over represented in selections for positions.
II.             Measurement of the Problem and Independent Variables
The dependent variable, hiring status, which is measured at the nominal level, where 1=hired and 2=not hired. The independent variable is race of the applicant, which is measured at the nominal level where 1=black and 2=non-­black. 
A control variable, residency of applicants, was used to see if the relationship between race and hiring status holds true, based on where applicants live. The control variable, residency of applicants, is measured at the nominal level, where 1=lives in Metro City and=resides outside of the city.
III.            Quantitative Approach Used
A Contingency Table Analysis (CTA) was used to test above hypothesis by determining if a statistically significant relationship existed between race and hire. This quantitative technique was used because the dependent variable (hiring status), the independent variable (race of applicant) and the control variable (residency) are all measured at the nominal level. 
IV.           Analysis of the Data
Table 1 presents a contingency table that assesses the influence of race of applicant on hiring for law enforcement patrolman positions.  
TABLE 1: ASSESSING THE IMPACT OF RACE ON POLICE HIRING
TABLE 1: ASSESSING THE IMPACT OF RACE ON POLICE HIRING
Chi Square; p=.03
Table 1 supports the above hypothesis in that it was expected that 22 black applicants would be hired yet the actual number of black applicants selected was a 28; 6 more applicants than expected. The Chi Square test of statistical significance suggests that we can be 97 percent confident that the difference between the expected and actual number of black applicants hired is attributed to race. 
Table 2 elaborates on Table 1 by examining the impact of race on hiring by municipal residency of applicants for patrolmen positions.  Since residency of an applicant could have an influence on hiring, a decision was made to statistically control for this variable to see if race continues to yield a systemic overrepresentation of black applicants in available patrolmen positions.   
To assess if the original hypothesis–that race impacts hiring–is statistically significant while considering residency of applicants, the expected and actual number of hires among black applicants are compared in Table 2. For example, it was expected that for applicants residing in the city, 12 black applicants would be hired and in actuality 16 black applicants were hired. Indeed, while there is over representation of black applicants who reside in city, the Chi Square test of statistical significance suggests that we can be 94.3 percent confident that the difference between the expected and actual number of black applicants hired is attributed to race for those applicants who live in the city.  Therefore, the impact of race on the difference between the expected and actual number of hires is considered random for applicants living in the city. 
TABLE 2: ASSESSING THE IMPACT OF RACE ON POLICE HIRINGBY RESIDENCY
Live in City, Chi Square; p=.057
Live Outside the City; p=. 302
I.               Decision Outcomes and Inquiry of Staff
The findings indicate that race does not have a systematic impact on hiring and the overrepresentation of hires of black applicants.  Instead, residency of the applicant has more of an influence on hiring. 
One question to ask Human Resources staff is: Does the city have a residency rule for hiring? If so, this policy can be influencing the hiring outcome.  Nonetheless, race is not a factor and the city should proceed with the hires. 

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