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Final Paper Needed, statistics homework help
The final project for this course is the creation of a statistical analysis report.
Each day, operations management profe ...
Final Paper Needed, statistics homework help
The final project for this course is the creation of a statistical analysis report.
Each day, operations management professionals are faced with multiple decisions affecting various aspects of the operation. The ability to use data to drive
decisions is an essential skill that is useful in any facet of an operation. The dynamic environment offers daily challenges that require the talents of the operations
manager; working in this field is exciting and rewarding.
Throughout the course, you will be engaged in activities that charge you with making decisions regarding inventory management, production capacity, product
profitability, equipment effectiveness, and supply chain management. These are just a few of the challenges encountered in the field of operations management.
The final activity in this course will provide you with the opportunity to demonstrate your ability to apply statistical tools and methods to solve a problem in a
given scenario that is often encountered by an operations manager. Once you have outlined your analysis strategy and analyzed your data, you will then report
your data, strategy, and overall decision that addresses the given problem.
The project is divided into two milestones, which will be submitted at various points throughout the course to scaffold learning and ensure quality final
submissions. These milestones will be submitted in Modules Three and Seven. The final project is due in Module Nine.
In this assignment, you will demonstrate your mastery of the following course outcomes:
Apply data-based strategies in guiding a focused approach for improving operational processes
Determine the appropriate statistical methods for informing valid data-driven decision making in professional settings
Select statistical tools for guiding data-driven decision making resulting in sustainable operational processes
Utilize a structured approach for data-driven decision making for fostering continuous improvement activities
Propose operational improvement recommendations to internal and external stakeholders based on relevant data
Prompt
Operations management professionals are often relied upon to make decisions regarding operational processes. Those who utilize a data-driven, structured
approach have a clear advantage over those offering decisions based solely on intuition. You will be provided with a scenario often encountered by an operations
manager. Your task is to review the “A-Cat Corp.: Forecasting” scenario, the addendum, and the accompanying data in the case scenario and addendum; outline
the appropriate analysis strategy; select a suitable statistical tool; and use data analysis to ultimately drive the decision. Once this has been completed, you will
be challenged to present your data, data analysis strategy, and overall decision in a concise report, justifying your analysis.
Specifically, the following critical elements must be addressed:
I. Introduction to the problem:
A. Provide a concise description of the scenario that you will be analyzing. The following questions might help you describe the scenario: What is
the type of organization identified in the scenario? What is the organization’s history and problem identified in the scenario? Who are the key
internal and external stakeholders?
II. Create an analysis plan to guide your analysis and decision making:
A. Identify any quantifiable factors that may be affecting the performance of operational processes. Provide a concise explanation of how these
factors may be affecting the operational processes.
B. Develop a problem statement that addresses the given problem in the scenario and contains quantifiable measures.
C. Propose a strategy that addresses the problem of the organization in the given case study and seeks to improve sustainable operational
processes. How will adjustments be identified and made?
III. Identify statistical tools and methods to collect data:
A. Identify the appropriate family of statistical tools that you will use to perform your analysis. What are your statistical assumptions concerning
the data that led you to selecting this family of tools? In other words, why did you select this family of tools for statistical analysis?
B. Determine the category of the provided data in the given case study. Be sure to justify why the data fits into this category type. What is the
relationship between the type of data and the tools?
C. From the identified family of statistical tools, select the most appropriate tool(s) for analyzing the data provided in the given case study.
D. Justify why you chose this tool to analyze the data. Be sure to include how this tool will help predict the use of the data in driving decisions.
E. Describe the quantitative method that will best inform data-driven decisions. Be sure to include how this method will point out the relationships
between the data. How will this method allow for the most reliable data?
IV. Analyze data to determine the appropriate decision for the identified problem:
A. Outline the process needed to utilize your statistical analysis to reach a decision regarding the given problem.
B. Explain how following this process leads to valid, data-driven decisions. In other words, why is following your outlined process important?
C. After analyzing the data sets in the case study, describe the reliability of the results. Be sure to include how you know whether the results are
reliable.
D. Illustrate a data-driven decision that addresses the given problem. How does your decision address the given problem? How will it result in
operational improvement?
V. Recommend operational improvements to stakeholders:
A. Summarize your analysis plan for both internal and external stakeholders. Be sure to use audience-appropriate jargon when summarizing for
both groups of stakeholders.
B. Explain how your decision addresses the given problem and how you reached that decision. Be sure to use audience-appropriate jargon for both
groups of stakeholders.
C. Justify why your decision is the best option for addressing the given problem to both internal and external stakeholders and how it will result in
operational improvement. Be sure to use audience-appropriate jargon when communicating with stakeholders.
Milestones
Milestone One: Introduction and Analysis Plan
In Module Three, you will submit your introduction and analysis plan, which are critical elements I and II. You will submit a 3- to 4-page paper that describes the
scenario provided in the case study, identifies quantifiable factors that may affect operational performance, develops a problem statement, and proposes a
strategy for resolving a company’s problem. This milestone will be graded with the Module One Rubric.
Milestone Two: Statistical Tools and Data Analysis
In Module Seven, you will submit your selection of statistical tools and data analysis, which are critical elements III and IV. You will submit a 3- to 4-page paper
and a spreadsheet that provides justification of the appropriate statistical tools that are needed to analyze the company’s data, a hypothesis, the results of your
analysis, any inferences from your hypothesis test, and a forecasting model that addresses the company’s problem. This milestone will be graded with the
Module Two Rubric.
Final Project Submission: Statistical Analysis Report
In Module Nine, you will submit your statistical analysis report and recommendations to management. It should be a complete, polished artifact containing all
of the critical elements of the final product. It should reflect the incorporation of feedback gained throughout the course. This submission will be graded with the
Final Project Rubric.
Final Project Rubric
Guidelines for Submission: Your statistical analysis report must be 10–12 pages in length (plus a cover page and references) and must be written in APA format.
Use double spacing, 12-point Times New Roman font, and one-inch margins. Include at least six references cited in APA format.
University Of California Los Angeles Testing Hypotheses for Means
To prepare for this Assignment: Review the Learning Resources and the media programs related to t tests.For additional su ...
University Of California Los Angeles Testing Hypotheses for Means
To prepare for this Assignment: Review the Learning Resources and the media programs related to t tests.For additional support, review the Skill Builder: Research Design and Statistical Design and the Skill Builder: Hypothesis Testing for Independent Samples t-test, which you can find by navigating back to your Blackboard Course Home Page. From there, locate the Skill Builder link in the left navigation pane.Also, review the t test scenarios found in this week’s Learning Resources and consider the three different approaches of t tests:Independent sample t testPaired sample t testOne sample t testBased on each of the three research scenarios provided, open the High School Longitudinal Study dataset or the Afrobarometer dataset from this week’s Learning Resources using SPSS software, then choose and run the appropriate t test.Once you perform your t test analyses, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document. For this Assignment: Write a 2 to 3-paragraph analysis of your t test results for each research scenario and include the SPSS syntax and output. If you are using the Afrobarometer Dataset, report the mean of Q1 (Age). If you are using the HS Long Survey Dataset, report the mean of X1Par1Edu. Do not forget to evaluate if the t test assumptions are met, justify the selection of type of t test, and report the effect size. Based on your results, provide an explanation of what the implications of social change might be. Use proper APA format, citations, and referencing for your analysis, research questions, and output. Notes from the instructor: Hi all, Here is an example of an RQ that would work for t-tests: RQ: Is there a difference in performance scores (DV) between males and females (IV)? When writing your hypotheses, remember that you need both a null and alternative hypothesis. The null states that there is no effect. The alternative states that there is an effect. How you write this depends on what type of test you are conducting. If you're conducting a comparison between groups, this might be an example: Ha: There is a difference in performance scores (DV) between males and females (IV). Ho: There is no difference in performance scores (DV) between males and females (IV). When conducting t-tests, the design that you will be using is typically experimental, quasi-experimental, causal-comparative, etc. Be sure to research these different types of designs so that you understand each one and how they differ from each other. When reporting t-tests, you want to use APA style like this: t(df) = xx.xx, p < .xx Here is an example: There was a significant effect for gender, t(54) = 5.43, p < .001, with women receiving higher scores than men. http://my.ilstu.edu/~jhkahn/apastats.html
Chamberlain College of Nursing Statistics Paper
Suppose that you have two sets of data to work with. The first set is a list of all the injuries that were seen in a clini ...
Chamberlain College of Nursing Statistics Paper
Suppose that you have two sets of data to work with. The first set is a list of all the injuries that were seen in a clinic in a month's time. The second set contains data on the number of minutes that each patient spent in the waiting room of a doctor's office. You can make assumptions about other information or variables that are included in each data set.For each data set, propose your idea of how best to represent the key information. To organize your data would you choose to use a frequency table, a cumulative frequency table, or a relative frequency table? Why?What type of graph would you use to display the organized data from each frequency distribution? What would be shown on each of the axes for each graph?it doesn't have to be long this is a weekly post
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Final Paper Needed, statistics homework help
The final project for this course is the creation of a statistical analysis report.
Each day, operations management profe ...
Final Paper Needed, statistics homework help
The final project for this course is the creation of a statistical analysis report.
Each day, operations management professionals are faced with multiple decisions affecting various aspects of the operation. The ability to use data to drive
decisions is an essential skill that is useful in any facet of an operation. The dynamic environment offers daily challenges that require the talents of the operations
manager; working in this field is exciting and rewarding.
Throughout the course, you will be engaged in activities that charge you with making decisions regarding inventory management, production capacity, product
profitability, equipment effectiveness, and supply chain management. These are just a few of the challenges encountered in the field of operations management.
The final activity in this course will provide you with the opportunity to demonstrate your ability to apply statistical tools and methods to solve a problem in a
given scenario that is often encountered by an operations manager. Once you have outlined your analysis strategy and analyzed your data, you will then report
your data, strategy, and overall decision that addresses the given problem.
The project is divided into two milestones, which will be submitted at various points throughout the course to scaffold learning and ensure quality final
submissions. These milestones will be submitted in Modules Three and Seven. The final project is due in Module Nine.
In this assignment, you will demonstrate your mastery of the following course outcomes:
Apply data-based strategies in guiding a focused approach for improving operational processes
Determine the appropriate statistical methods for informing valid data-driven decision making in professional settings
Select statistical tools for guiding data-driven decision making resulting in sustainable operational processes
Utilize a structured approach for data-driven decision making for fostering continuous improvement activities
Propose operational improvement recommendations to internal and external stakeholders based on relevant data
Prompt
Operations management professionals are often relied upon to make decisions regarding operational processes. Those who utilize a data-driven, structured
approach have a clear advantage over those offering decisions based solely on intuition. You will be provided with a scenario often encountered by an operations
manager. Your task is to review the “A-Cat Corp.: Forecasting” scenario, the addendum, and the accompanying data in the case scenario and addendum; outline
the appropriate analysis strategy; select a suitable statistical tool; and use data analysis to ultimately drive the decision. Once this has been completed, you will
be challenged to present your data, data analysis strategy, and overall decision in a concise report, justifying your analysis.
Specifically, the following critical elements must be addressed:
I. Introduction to the problem:
A. Provide a concise description of the scenario that you will be analyzing. The following questions might help you describe the scenario: What is
the type of organization identified in the scenario? What is the organization’s history and problem identified in the scenario? Who are the key
internal and external stakeholders?
II. Create an analysis plan to guide your analysis and decision making:
A. Identify any quantifiable factors that may be affecting the performance of operational processes. Provide a concise explanation of how these
factors may be affecting the operational processes.
B. Develop a problem statement that addresses the given problem in the scenario and contains quantifiable measures.
C. Propose a strategy that addresses the problem of the organization in the given case study and seeks to improve sustainable operational
processes. How will adjustments be identified and made?
III. Identify statistical tools and methods to collect data:
A. Identify the appropriate family of statistical tools that you will use to perform your analysis. What are your statistical assumptions concerning
the data that led you to selecting this family of tools? In other words, why did you select this family of tools for statistical analysis?
B. Determine the category of the provided data in the given case study. Be sure to justify why the data fits into this category type. What is the
relationship between the type of data and the tools?
C. From the identified family of statistical tools, select the most appropriate tool(s) for analyzing the data provided in the given case study.
D. Justify why you chose this tool to analyze the data. Be sure to include how this tool will help predict the use of the data in driving decisions.
E. Describe the quantitative method that will best inform data-driven decisions. Be sure to include how this method will point out the relationships
between the data. How will this method allow for the most reliable data?
IV. Analyze data to determine the appropriate decision for the identified problem:
A. Outline the process needed to utilize your statistical analysis to reach a decision regarding the given problem.
B. Explain how following this process leads to valid, data-driven decisions. In other words, why is following your outlined process important?
C. After analyzing the data sets in the case study, describe the reliability of the results. Be sure to include how you know whether the results are
reliable.
D. Illustrate a data-driven decision that addresses the given problem. How does your decision address the given problem? How will it result in
operational improvement?
V. Recommend operational improvements to stakeholders:
A. Summarize your analysis plan for both internal and external stakeholders. Be sure to use audience-appropriate jargon when summarizing for
both groups of stakeholders.
B. Explain how your decision addresses the given problem and how you reached that decision. Be sure to use audience-appropriate jargon for both
groups of stakeholders.
C. Justify why your decision is the best option for addressing the given problem to both internal and external stakeholders and how it will result in
operational improvement. Be sure to use audience-appropriate jargon when communicating with stakeholders.
Milestones
Milestone One: Introduction and Analysis Plan
In Module Three, you will submit your introduction and analysis plan, which are critical elements I and II. You will submit a 3- to 4-page paper that describes the
scenario provided in the case study, identifies quantifiable factors that may affect operational performance, develops a problem statement, and proposes a
strategy for resolving a company’s problem. This milestone will be graded with the Module One Rubric.
Milestone Two: Statistical Tools and Data Analysis
In Module Seven, you will submit your selection of statistical tools and data analysis, which are critical elements III and IV. You will submit a 3- to 4-page paper
and a spreadsheet that provides justification of the appropriate statistical tools that are needed to analyze the company’s data, a hypothesis, the results of your
analysis, any inferences from your hypothesis test, and a forecasting model that addresses the company’s problem. This milestone will be graded with the
Module Two Rubric.
Final Project Submission: Statistical Analysis Report
In Module Nine, you will submit your statistical analysis report and recommendations to management. It should be a complete, polished artifact containing all
of the critical elements of the final product. It should reflect the incorporation of feedback gained throughout the course. This submission will be graded with the
Final Project Rubric.
Final Project Rubric
Guidelines for Submission: Your statistical analysis report must be 10–12 pages in length (plus a cover page and references) and must be written in APA format.
Use double spacing, 12-point Times New Roman font, and one-inch margins. Include at least six references cited in APA format.
University Of California Los Angeles Testing Hypotheses for Means
To prepare for this Assignment: Review the Learning Resources and the media programs related to t tests.For additional su ...
University Of California Los Angeles Testing Hypotheses for Means
To prepare for this Assignment: Review the Learning Resources and the media programs related to t tests.For additional support, review the Skill Builder: Research Design and Statistical Design and the Skill Builder: Hypothesis Testing for Independent Samples t-test, which you can find by navigating back to your Blackboard Course Home Page. From there, locate the Skill Builder link in the left navigation pane.Also, review the t test scenarios found in this week’s Learning Resources and consider the three different approaches of t tests:Independent sample t testPaired sample t testOne sample t testBased on each of the three research scenarios provided, open the High School Longitudinal Study dataset or the Afrobarometer dataset from this week’s Learning Resources using SPSS software, then choose and run the appropriate t test.Once you perform your t test analyses, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document. For this Assignment: Write a 2 to 3-paragraph analysis of your t test results for each research scenario and include the SPSS syntax and output. If you are using the Afrobarometer Dataset, report the mean of Q1 (Age). If you are using the HS Long Survey Dataset, report the mean of X1Par1Edu. Do not forget to evaluate if the t test assumptions are met, justify the selection of type of t test, and report the effect size. Based on your results, provide an explanation of what the implications of social change might be. Use proper APA format, citations, and referencing for your analysis, research questions, and output. Notes from the instructor: Hi all, Here is an example of an RQ that would work for t-tests: RQ: Is there a difference in performance scores (DV) between males and females (IV)? When writing your hypotheses, remember that you need both a null and alternative hypothesis. The null states that there is no effect. The alternative states that there is an effect. How you write this depends on what type of test you are conducting. If you're conducting a comparison between groups, this might be an example: Ha: There is a difference in performance scores (DV) between males and females (IV). Ho: There is no difference in performance scores (DV) between males and females (IV). When conducting t-tests, the design that you will be using is typically experimental, quasi-experimental, causal-comparative, etc. Be sure to research these different types of designs so that you understand each one and how they differ from each other. When reporting t-tests, you want to use APA style like this: t(df) = xx.xx, p < .xx Here is an example: There was a significant effect for gender, t(54) = 5.43, p < .001, with women receiving higher scores than men. http://my.ilstu.edu/~jhkahn/apastats.html
Chamberlain College of Nursing Statistics Paper
Suppose that you have two sets of data to work with. The first set is a list of all the injuries that were seen in a clini ...
Chamberlain College of Nursing Statistics Paper
Suppose that you have two sets of data to work with. The first set is a list of all the injuries that were seen in a clinic in a month's time. The second set contains data on the number of minutes that each patient spent in the waiting room of a doctor's office. You can make assumptions about other information or variables that are included in each data set.For each data set, propose your idea of how best to represent the key information. To organize your data would you choose to use a frequency table, a cumulative frequency table, or a relative frequency table? Why?What type of graph would you use to display the organized data from each frequency distribution? What would be shown on each of the axes for each graph?it doesn't have to be long this is a weekly post
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