Description
Which equation is represented by the graph? https://tcan4424-oakcliff-ccl.gradpoint.com/Resour... | |||||||||||||||||||||||||||||||||
|
User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.
Explanation & Answer
1. Graph is represented by, y = |x| - 1.
Option C
2. Option A i.e. point (4,7) is the solution of given inequality y > |-x+4| + 1
3. Let say, money spent = k * number of tickets
where k = constant of variation
therefore, k = money spent / number of tickets
k = 48/6
k = 8
Option A
Completion Status:
100%
Review
Review
Anonymous
I was stuck on this subject and a friend recommended Studypool. I'm so glad I checked it out!
Studypool
4.7
Trustpilot
4.5
Sitejabber
4.4
24/7 Homework Help
Stuck on a homework question? Our verified tutors can answer all questions, from basic math to advanced rocket science!
Most Popular Content
Multiple Logistic Regression in Action Report
Assignment: Multiple Logistic Regression in Action
Multiple logistic regression is a model that uses analysis of predictor ...
Multiple Logistic Regression in Action Report
Assignment: Multiple Logistic Regression in Action
Multiple logistic regression is a model that uses analysis of predictor variables to make predictions as to the likelihood of occurrences of an outcome.
For this Assignment, you use multiple logistic regression to analyze a dataset. You identify assumptions required by multiple logistic regression and evaluate whether they have been met by the data. Finally, you interpret your results and evaluate the use of multiple logistic regression.
The Assignment
Use the Week 7 Dataset (SPSS document) from the Learning Resources area to complete this assignment.
Variables and variable selection (20 Points)
Use a table to list the variables, Sex, Age in Years, Serum Cholesterol, Obese, and Hypertension, and each of their levels of measurement. (10 Points)
Create new variables Age_Cat and Chole_Cat:
Age_Cat: Convert Age in Years into a categorical variable with 2 categories, Less than 40, 40 and greater
Chole_Cat: Convert Serum Cholesterol into 3 categories, Under 200, 200-299, and 300 and greater
Add the new variables to each record by coding the responses to the original variable using the assigned categories. Be sure that the variable view in SPSS has the correct information on the 2 new variables. (10 Points)
Simple Binary Logistic Regression (30 Points)
Use Hypertension as the dependent variable and Chole_Cat as the independent variable in the first model. Report the Odds Ratio and significance of the Odds Ratio for the relationship between the dependent and independent variables. (10 Points)
Use Hypertension as the dependent variable and Serum Cholesterol (the original variable) as the independent variable in the second model. Report the Odds Ratio and significance of the Odds Ratio for the relationship between the dependent and independent variables. (10 Points)
How does the level of measurement for the independent variable affect the outcome (include the OR and its significance in your response)? How does the level of measurement of the independent variable change your interpretation of the Odds Ratio? (10 Points)
Multivariate Logistic Regression (50 Points)
Run a multivariate binary logistic regression model using SPSS and Hypertension as the dependent variable, Chole_Cat, Age_Cat, Obese, and Sex as the Covariates. Include the output in your submission. (10 Points)
Identify the Odds Ratio and the significance of the Odds Ratio for each of the covariates. How has the relationship between Chole_Cat and Hypertension changed with the addition of the other variables (compare to the output from # 2a)? (15 Points)
Test the assumption that the model fits the data using the Hosmer-Lemeshow Goodness of Fit test. Interpret the Chi Square statistic given in the output of this test and state what it means in terms of the assumptions needed to use logistic regression with this data. (10 Points)
Rerun the logistic regression model from #3a and use the save function to create the following new variables: Predicted Probabilities, Deviance Residuals, and Cook’s Distance. Evaluate the model using these saved variables and the following Scatter Plots. (15 Points)
Create a Scatter Plot of the Deviance Residuals (DEV) and the variable ID: Are there any outliers? What does this mean when evaluating your model?
Create a Scatter Plot of Cook’s Distance (COO) and the variable ID: Are there any influential cases? What does this mean when evaluating your model?
Create a Scatter Plot of Deviance (DEV) and the Predicted Probabilities (PRE). Discuss whether anything in this scatterplot could cause you some concern in terms of your model.
9 pages
Multiple Linear Regression Model
Multiple linear regression model is basically a statistical approach that make use of several independent or explanatory v ...
Multiple Linear Regression Model
Multiple linear regression model is basically a statistical approach that make use of several independent or explanatory variables to predict the ...
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.
INFO 1260 CS 1340 Cornell College Ranking and Attention Question
If you have any questions about the homework assignment and would like to see some of the readings I can send you them but ...
INFO 1260 CS 1340 Cornell College Ranking and Attention Question
If you have any questions about the homework assignment and would like to see some of the readings I can send you them but you are able to do the homework assignment without having done the readings.
RSCH 8210 Walden University Week 3 Central Tendency and Variability Discussion
Central Tendency and VariabilityRequired ReadingsFrankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social sta ...
RSCH 8210 Walden University Week 3 Central Tendency and Variability Discussion
Central Tendency and VariabilityRequired ReadingsFrankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society (9th ed.). Thousand Oaks, CA: Sage Publications.Chapter 3, “Measures of Central Tendency” (pp. 75-111)Chapter 4, “Measures of Variability” (pp. 113-150)Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.Chapter 4, “Organization and Presentation of Information”Chapter 11, “Editing Output”Wheelan, C. (2013). Naked statistics: Stripping the dread from data. New York, NY: W. W. Norton & Company.By Day 3Post, present, and report a descriptive analysis for your variables, specifically noting the following UNDER EACH HEADINGFor your continuous variable:Report the mean, median, and mode.What might be the better measure for central tendency? (i.e., mean, median, or mode) and why?Report the standard deviation.How variable are the data?How would you describe this data?What sort of research question would this variable help answer that might inform social change?Post the following information for your categorical variable:A frequency distribution.An appropriate measure of variation.How variable are the data?How would you describe this data?What sort of research question would this variable help answer that might inform social change?Be sure to support your Main Post and Response Post with reference to the week’s Learning Resources and other scholarly evidence in APA 7 Writing Style.By Day 5Respond to at least one colleagues’ post with a comment on the presentation and interpretation of their analysis. In your response, address the following questions: ADDRESS UNDER EACH HEADINGWas the presentation of results clear? If so, provide some specific comments on why. If not, provide constructive suggestions.Are you able to understand how the results might relate back to positive social change? Do you think there are other aspects of positive social change related to the results?Thanks much!
Similar Content
SUNY Morrisville Pre Calculus Algebraic Operations Exam Exercises
Greetings I have a pre calc exam I need help with that is 20 questions, thank you....
Descriptive Statistics-Excel
Descriptive Statistics Identify a research problem different from the previous research problems that uses two different s...
Short small easy math discussion
Write a response to any of the following.Would you be more likely to play a game with a greater chance of winning a small ...
System of Congruences, math homework help
Explain why a solution does not exist for the following systems of congruences. Your work should include reduction to a si...
Discrete Probability Statistics Applications Worksheet
2 Questions I need help with for my statistics class:Question 1 - Creating a discrete probability distribution: A venture ...
Skyline College Algebra Questions
Solve the inequality. (Enter your answer using interval notation.)
0 <
x + 4
3
< 2
-4< < 2
Graph the solution set on the r...
Related Tags
Book Guides
Get 24/7
Homework help
Our tutors provide high quality explanations & answers.
Post question
Most Popular Content
Multiple Logistic Regression in Action Report
Assignment: Multiple Logistic Regression in Action
Multiple logistic regression is a model that uses analysis of predictor ...
Multiple Logistic Regression in Action Report
Assignment: Multiple Logistic Regression in Action
Multiple logistic regression is a model that uses analysis of predictor variables to make predictions as to the likelihood of occurrences of an outcome.
For this Assignment, you use multiple logistic regression to analyze a dataset. You identify assumptions required by multiple logistic regression and evaluate whether they have been met by the data. Finally, you interpret your results and evaluate the use of multiple logistic regression.
The Assignment
Use the Week 7 Dataset (SPSS document) from the Learning Resources area to complete this assignment.
Variables and variable selection (20 Points)
Use a table to list the variables, Sex, Age in Years, Serum Cholesterol, Obese, and Hypertension, and each of their levels of measurement. (10 Points)
Create new variables Age_Cat and Chole_Cat:
Age_Cat: Convert Age in Years into a categorical variable with 2 categories, Less than 40, 40 and greater
Chole_Cat: Convert Serum Cholesterol into 3 categories, Under 200, 200-299, and 300 and greater
Add the new variables to each record by coding the responses to the original variable using the assigned categories. Be sure that the variable view in SPSS has the correct information on the 2 new variables. (10 Points)
Simple Binary Logistic Regression (30 Points)
Use Hypertension as the dependent variable and Chole_Cat as the independent variable in the first model. Report the Odds Ratio and significance of the Odds Ratio for the relationship between the dependent and independent variables. (10 Points)
Use Hypertension as the dependent variable and Serum Cholesterol (the original variable) as the independent variable in the second model. Report the Odds Ratio and significance of the Odds Ratio for the relationship between the dependent and independent variables. (10 Points)
How does the level of measurement for the independent variable affect the outcome (include the OR and its significance in your response)? How does the level of measurement of the independent variable change your interpretation of the Odds Ratio? (10 Points)
Multivariate Logistic Regression (50 Points)
Run a multivariate binary logistic regression model using SPSS and Hypertension as the dependent variable, Chole_Cat, Age_Cat, Obese, and Sex as the Covariates. Include the output in your submission. (10 Points)
Identify the Odds Ratio and the significance of the Odds Ratio for each of the covariates. How has the relationship between Chole_Cat and Hypertension changed with the addition of the other variables (compare to the output from # 2a)? (15 Points)
Test the assumption that the model fits the data using the Hosmer-Lemeshow Goodness of Fit test. Interpret the Chi Square statistic given in the output of this test and state what it means in terms of the assumptions needed to use logistic regression with this data. (10 Points)
Rerun the logistic regression model from #3a and use the save function to create the following new variables: Predicted Probabilities, Deviance Residuals, and Cook’s Distance. Evaluate the model using these saved variables and the following Scatter Plots. (15 Points)
Create a Scatter Plot of the Deviance Residuals (DEV) and the variable ID: Are there any outliers? What does this mean when evaluating your model?
Create a Scatter Plot of Cook’s Distance (COO) and the variable ID: Are there any influential cases? What does this mean when evaluating your model?
Create a Scatter Plot of Deviance (DEV) and the Predicted Probabilities (PRE). Discuss whether anything in this scatterplot could cause you some concern in terms of your model.
9 pages
Multiple Linear Regression Model
Multiple linear regression model is basically a statistical approach that make use of several independent or explanatory v ...
Multiple Linear Regression Model
Multiple linear regression model is basically a statistical approach that make use of several independent or explanatory variables to predict the ...
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.
INFO 1260 CS 1340 Cornell College Ranking and Attention Question
If you have any questions about the homework assignment and would like to see some of the readings I can send you them but ...
INFO 1260 CS 1340 Cornell College Ranking and Attention Question
If you have any questions about the homework assignment and would like to see some of the readings I can send you them but you are able to do the homework assignment without having done the readings.
RSCH 8210 Walden University Week 3 Central Tendency and Variability Discussion
Central Tendency and VariabilityRequired ReadingsFrankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social sta ...
RSCH 8210 Walden University Week 3 Central Tendency and Variability Discussion
Central Tendency and VariabilityRequired ReadingsFrankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society (9th ed.). Thousand Oaks, CA: Sage Publications.Chapter 3, “Measures of Central Tendency” (pp. 75-111)Chapter 4, “Measures of Variability” (pp. 113-150)Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.Chapter 4, “Organization and Presentation of Information”Chapter 11, “Editing Output”Wheelan, C. (2013). Naked statistics: Stripping the dread from data. New York, NY: W. W. Norton & Company.By Day 3Post, present, and report a descriptive analysis for your variables, specifically noting the following UNDER EACH HEADINGFor your continuous variable:Report the mean, median, and mode.What might be the better measure for central tendency? (i.e., mean, median, or mode) and why?Report the standard deviation.How variable are the data?How would you describe this data?What sort of research question would this variable help answer that might inform social change?Post the following information for your categorical variable:A frequency distribution.An appropriate measure of variation.How variable are the data?How would you describe this data?What sort of research question would this variable help answer that might inform social change?Be sure to support your Main Post and Response Post with reference to the week’s Learning Resources and other scholarly evidence in APA 7 Writing Style.By Day 5Respond to at least one colleagues’ post with a comment on the presentation and interpretation of their analysis. In your response, address the following questions: ADDRESS UNDER EACH HEADINGWas the presentation of results clear? If so, provide some specific comments on why. If not, provide constructive suggestions.Are you able to understand how the results might relate back to positive social change? Do you think there are other aspects of positive social change related to the results?Thanks much!
Earn money selling
your Study Documents