Posted: June 6th, 2022

Recomendations

instructions
ATTACHED FILE(S)
Recommendations
Introduction
So far, for your course project, you have identified a problem and analyzed data to better understand that problem. Now the question is: what should be done? This is the decision-making part of data analytics.
Instructions
Workingindependently(that is, without your group members), propose three to five recommendations based on what you have found. Your recommendations should be clearly identified, and you must provide a rationale for each recommendation.
Include the following sections in this assignment:
· Identification of the Problem:
. Summarize the problem in no more than one paragraph.
· Summary of Data Analysis:
. Summarize the quantitative analysis (what was done and the findings) in one paragraph. (No tables or charts should be presented here.)
. Summarize the qualitative analysis in one paragraph.
· Recommendations:
. Clearly identify each recommendation.
. Provide a rationale for each recommendation.
This assignment should be 3–5 pages long. It should be well organized and free of mechanical errors (errors in grammar, punctuation, and APA format).
Problem Identification and Model Planning

Problem Identification and Model Planning
Identification of the Problem
The problem selected is whether there was a difference in levels of family conflict for those who received legal support compared to those who did not. Teens involved in the juvenile system are more likely than their peers to experience family conflicts and negative life outcomes. Notably, these youths have greater risks of emotional and mental health issues, occupational problems, and educational difficulties. Consequently, they cannot defend themselves and must be represented by an attorney in criminal proceedings. However, not all juvenile offenders receive child-friendly legal aid, which reduces their access to justice. It is important to learn about the role of legal support in improving a child’s ability to reintegrate and rehabilitate after the proceedings and how this might shield against family conflict to help with the homelessness program. Homeless Teen Program director and staff believe that the approach to addressing the roots of homeless is the key source of the program’s success. Family problems are the main focus, given the role of family support in reducing homelessness. Therefore, increasing Helping Hands’ understanding of the connection between legal support among juvenile offenders and family conflicts helps them understand the need for family intervention.
The data analytics process can be useful for analyzing family conflict trends among teens with a history of juvenile system involvement. For instance, it will help the program team to obtain insights into predictive factors that led to homeless, such as the number of homeless teens who have been involved in the juvenile system, teens who received legal support after the involvement, the number of stays in the system, interactions with family, and how those who received legal support are responding to program compared to those who did not. The six phases of the data analytic life cycle include discovery, data preparation, model planning, model building, communicating results, and operationalizing (Services, 2015). These phases will help the team determine whether it is appropriate to stay in the current state or move to the next.
Identification of Data Needed
The quantitative data used to evaluate the problem include age, the number of stays in the juvenile justice system, number of teens who had conflicts with their families after returning from the system, frequency of the conflict, enrollment in the support system, and attendance. These variables are appropriate because they will help the team identify whether receiving legal support after involving in the juvenile system can serve as protective agents against the impact of the system on family conflicts. Linear regression analysis would be appropriate because it shows how strong the relationship between two variables is.
The qualitative data that would be helpful include parental attitudes, parenting style, physical violence, degree of family cohesion, and other factors that affect child character development. There are also non-family factors such as lack of access to legal support, failure juvenile justice system, drug abuse, mental health problems, genetic problems, and poverty. These variables are appropriate in determining the frequency of characteristics that help understand participants better. Content analysis is important in quantifying and analyzing relationships, meanings and the presence of specific concepts, themes and words to determine bias (Colombia University, 2019). It is conducted by selecting content to analyze, defining analysis categories and units, establishing coding rules, processing the text based on the rules, evaluating the results, and deriving inferences.
Group Collaboration
We formed the group by setting clear group goals, considering steps to achieve these goals, determining flexible ground rules for group cohesion, creating group roles, building trust and promoting open communication, and initiating discussions. Group collaboration improved my understanding of the problem by exposing me to diverse perspectives and enhancing my vocabulary responsibility and critical thinking.

References
Colombia University. (2019). Content Analysis. https://www.publichealth.columbia.edu/research/population-health-methods/content-analysis#:~:text=Using%20content%20analysis%2C%20researchers%20can,search%20for%20bias%20or%20partiality.
Services, EMC. (2015). Data Analytics Lifecycle. 10.1002/9781119183686.ch2.

Model Building
Statistical and content analyses
Identification of the problem
The problem that our group identified to use for this assignment is the difference in the levels of family conflict for those who received legal support compared to those who didn’t. this has been a major challenge in several communities that have led to children being homeless. This is because; teens who are involved in the juvenile systems are more probably than their fellows to encounter family conflicts and negative life outcomes. Through this, these youths are at a greater risk for mental and emotional issues since they are subjected to these settings.
Quantitative analyses
Data and variable type
Both data and variable types were categorical. This is because; the collection of data was divided into groups. The data of juvenile teens was dived into two; the juvenile who received government support and the ones who didn’t receive government support. These data were categorized into two to determine the distinction between the two data. (Goss-Sampson, 2019) On the other hand; the type of variable that this assignment used was categorical; the population was divided into groups which were in terms of race, sex age group, and educational level.
Type of statistical analysis that was used
The statistical analysis that we employed was statistical interference. This is the procedure through which implications about a population are made founded on certain data premeditated from a sample of data drawn from that people. This statistical analysis allowed us to test the hypothesis and we were in a pole position to conclude the data. We examined the entire data of the population, we applied the results to the group as a whole. We combined the results of the two groups of teens who have gone through the juvenile system. These implied both groups; the ones who were supported by the government and the ones who were not supported by the government. (Marees, et al. 2019)
Results
Out of the two groups; the one who was supported by the government after passing through the juvenile system; 20 percent said they lived a good life, and 60 percent said they were able to manage the conflicts between them and their family. They were also able to be accepted back into the community while only 20 percent said they faced the challenges of being homeless. On the other hand, the group of teens who passed through the juvenile system were not supported by the government. There was a high percentage of them being homeless, which was represented by the 60percent, 20 percent experienced emotional and mental health issues while 20 percent experienced rejection from their families.
Teens supported by the government

Groups

Percentage (%)

Lived a healthy life

20

Able to manage conflicts in their families

60

Accepted back in the community

20

Total

100
Teens who were not supported by the government

Groups

Percentage (%)

Challenges of homeless

60

Emotional and mental health issues

20

Rejection from their families

20

Total

100
Significance of testing
The significance of these testing was to approximation the possibility that a association observed in the information happened only by chance, the possibility that the variables were unconnected in the population. This also helped to filter out uncompromising hypotheses. Additionally, the significance of this testing helped to establish a mutual yardstick that was assumed by greater many individuals, and they communicated vital data about the research project. (Mrkvička, et al. 2021)
A possible implication of the findings
Homelessness and family conflicts have been major issues that the community faces every day. This can be triggered by the aspects of children going to the juvenile system. When a child goes through a juvenile system, back in society, a child is seen as a criminal. This is a huge call for the government to try and support these teens when they are through their juvenile system. The implications of these results will be in non-governmental organizations whole trying to solve the issue within the society. Additionally, this information will be beneficial to the government in the allocation of resources. This will aid the allocation of resources in a way that there will be more resources that will be directed to the community with a high percentage of homelessness and conflicts within the families.
Content analysis
Identify the data
The data that was employed in content analysis is homelessness and conflicts in the families. These two issues have been a major challenge to the community since they drag the community behind in a way that there is the rise of issues that lead to issues such as poverty and discrimination. (Lindgren, et al. 2020)
Results of the content analysis
More than half (60 percent) of those who were supported by government services after completing the juvenile justice system reported that they were able to handle their family disputes. When they returned to society, only 20% of them indicated they had to deal with the difficulties of being homeless. When it comes to teenagers who were not supported by the government, however, the situation is rather different. 60 percent of them were homeless, 20 percent had emotional and mental health concerns, and 20 percent had been rejected by their family, according to the findings.
Themes
The themes that we employed in the content analysis include; the theme of forgiveness and acceptance. Those two themes are important in this data analysis since they offer a great opportunity for children who pass through the juvenile system either be supported or not to be accepted back into the community. Through this, there will be a reduction in family conflicts among teens and family members. The theme of
forgiveness implies that teens who go through juvenile systems should be forgiven by their community members and family members so that they will be given another chance to be able to rectify their wrongdoings and have a fresh start.
Illustrative quotation of the themes
The illustrative quotation of the theme of forgiveness is that the research found out that many teens who have passed through a juvenile system were at risk of developing emotional and mental issues. This was a result of homelessness and being rejected by the community and family members. Through this, these teens found themselves in a hard situation trying to manage their education and living in a community where they are seen as criminals. (Siraj, 2019)
A possible implication of these findings
The neighborhood has to deal with homelessness and family strife daily. Juvenile delinquency can have a role in this. Back in society, a child who has been through the juvenile justice system is viewed as a criminal. This is a strong call to action for the federal government to assist these young people as they navigate the juvenile justice system. As a result of these findings, nongovernmental organizations working to address social problems will be impacted. Additionally, the government will benefit from this knowledge when it comes to allocating funds. This will make it easier to allocate resources so that more money may go to areas where there is a high rate of homelessness and family strife.
References
Goss-Sampson, M. (2019). Statistical analysis in JASP: A guide for students.
Marees, A. T., de Kluiver, H., Stringer, S., Vorspan, F., Curis, E., Marie‐Claire, C., & Derks, E. M. (2018). A tutorial on conducting genome‐wide association studies: Quality control and statistical analysis.International journal of methods in psychiatric research,27(2), e1608.
Mrkvička, T., Roskovec, T., & Rost, M. (2021). A nonparametric graphical test of significance in functional GLM. Methodology and Computing in Applied Probability,23(2), 593-612.
Lindgren, B. M., Lundman, B., & Graneheim, U. H. (2020). Abstraction and interpretation during the qualitative content analysis process.International journal of nursing studies,108, 103632.
Siraj, N. B., & Fayek, A. R. (2019). Risk identification and common risks in construction: Literature review and content analysis.Journal of Construction Engineering and Management,145(9), 03119004.

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