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Assume the known fact that the square root of five is irrational and prove ( by indirect proof) that the Golden Ratio we have called G is also irrational.
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Walden University High School Longitudinal Study Dataset Discussion
Whether in a scholarly or practitioner setting, good research and data analysis should have the benefit of peer feedback. ...
Walden University High School Longitudinal Study Dataset Discussion
Whether in a scholarly or practitioner setting, good research and data analysis should have the benefit of peer feedback. For this Discussion, you will post your response to the hypothesis test, along with the results. Be sure and remember that the goal is to obtain constructive feedback to improve the research and its interpretation, so please view this as an opportunity to learn from one another. To prepare for this Discussion: Review this week’s Learning Resources and media program related to multiple regression. Create a research question using the Afrobarometer Dataset or the HS Long Survey Dataset, that can be answered by multiple regression. Use SPSS to answer the research questions. 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 X1SES. What is your research question? What is the null hypothesis for your question? What research design would align with this question? What dependent variable was used and how is it measured? What independent variables are used and how are they measured? What is the justification for including these predictor variables? If you found significance, what is the strength of the effect? Explain your results for a lay audience, explain what the answer to your research question. Be sure to support your Main Post and Response Post with reference to the week’s Learning Resources and other scholarly evidence in APA Style.Learning ResourcesRequired ReadingsFrankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society (9th ed.). Thousand Oaks, CA: Sage Publications.Chapter 12, “Regression and Correlation” (pp. 401-457) (previously read in Week 8)Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.Chapter 8, "Correlation and Regression Analysis"Chapter 11, “Editing Output” (previously read in Week 2, 3, 4, 5. 6, 7, and 8)Walden University Library. (n.d.). Course Guide and Assignment Help for RSCH 8210. Retrieved from http://academicguides.waldenu.edu/rsch8210For help with this week’s research, see this Course Guide and related weekly assignment resources.Document: Walden University: Research Design Alignment TableRequired MediaLaureate Education (Producer). (2016g). Multiple regression [Video file]. Baltimore, MD: Author.Note: The approximate length of this media piece is 7 minutes.In this media program, Dr. Matt Jones demonstrates multiple regression using the SPSS software.Accessible player --Downloads-- Download Video w/CC Download Audio Download Transcript Optional ResourcesSkill Builder: Interpreting the Results from Regression ModelsTo access these Skill Builders, navigate back to your Blackboard Course Home page, and locate “Skill Builders” in the left navigation pane. From there, click on the relevant Skill Builder link for this week. You are encouraged to click through these and all Skill Builders to gain additional practice with these concepts. Doing so will bolster your knowledge of the concepts you’re learning this week and throughout the course.
13 pages
Question Set F
Download the Excel data of E-commerce Retail Sales and follow the steps below for time series forecasting. To be able to r ...
Question Set F
Download the Excel data of E-commerce Retail Sales and follow the steps below for time series forecasting. To be able to receive full credit, you must ...
Missing Data
This week’s Learning Resources include several different ways to identify and assess the issue of missing data in your d ...
Missing Data
This week’s Learning Resources include several different ways to identify and assess the issue of missing data in your database. From your assessment and knowledge of possible ways to manipulate data, and to overcome potential challenges presented by the missing data, you will be able to analyze and reach conclusions about your analysis. It is important to recognize when and how to apply the most viable solution to the missing data. In addition, it is important to learn to recognize when your data results could be compromised by missing data.For this, you will analyze the impact of missing data on data analysis.To prepare:Review this week’s Learning Resources.Analysis of missing data. Include the following in your post:An explanation of the importance of handling missing data and skipping patterns and how missing data can affect data analysisA technique on how you may handle missing data appropriately with an explanation of why this technique worksChoose one of the variables you selected for your Scholar-Practitioner Project (select one with missing values) and report proportion of missing for that variableIndicate the possible reason for the missing values in that variable.ReferencesWang, R., Sedransk, J., & Jinn, J. H. (1992). Secondary data analysis when there are missing observations. Journal of the American Statistical Association, 7(420), 952–961. Long, J. A., Bamba, M. I., Ling, B., & Shea, J. A. (2006). Missing race/ethnicity data in Veterans Health Administration based disparities research: A systematic review. Journal of Health Care for the Poor and Underserved, 17(1), 128–140.Langkamp, D. L., Lehman, A., & Lemeshow, S. (2010). Techniques for handling missing data in secondary analyses of large surveys. Academic Pediatrics, 10(3), 205–210.
CSU Mod 2 Coefficient of Variation & Standard Deviation Research
The coefficient of variation and the standard deviation are two measures of variability or dispersion among data values. P ...
CSU Mod 2 Coefficient of Variation & Standard Deviation Research
The coefficient of variation and the standard deviation are two measures of variability or dispersion among data values. Provide two different sets of ten data points each as examples. Calculate the standard deviation and coefficient of variation for each data set, being sure to attach your Excel file to show your work. Explain which of the two mentioned measures can more accurately specify which of these two data sets has more variability or dispersion in their data values and why.Research the method behind the Excel function “QUARTILE.EXC” for calculating quartiles for a given data set. Summarize this method in your own words and discuss how it differs from the method presented in the textbook and lecture.Your document should be minimum 400 words. Please have credible references.
5 pages
Deliverable 4 Questions Final Copy
1. Describe the 8 steps in the process for hypothesis testing. Explain the decision criteria for rejecting the null hypoth ...
Deliverable 4 Questions Final Copy
1. Describe the 8 steps in the process for hypothesis testing. Explain the decision criteria for rejecting the null hypothesis for both the p-value ...
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Most Popular Content
Walden University High School Longitudinal Study Dataset Discussion
Whether in a scholarly or practitioner setting, good research and data analysis should have the benefit of peer feedback. ...
Walden University High School Longitudinal Study Dataset Discussion
Whether in a scholarly or practitioner setting, good research and data analysis should have the benefit of peer feedback. For this Discussion, you will post your response to the hypothesis test, along with the results. Be sure and remember that the goal is to obtain constructive feedback to improve the research and its interpretation, so please view this as an opportunity to learn from one another. To prepare for this Discussion: Review this week’s Learning Resources and media program related to multiple regression. Create a research question using the Afrobarometer Dataset or the HS Long Survey Dataset, that can be answered by multiple regression. Use SPSS to answer the research questions. 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 X1SES. What is your research question? What is the null hypothesis for your question? What research design would align with this question? What dependent variable was used and how is it measured? What independent variables are used and how are they measured? What is the justification for including these predictor variables? If you found significance, what is the strength of the effect? Explain your results for a lay audience, explain what the answer to your research question. Be sure to support your Main Post and Response Post with reference to the week’s Learning Resources and other scholarly evidence in APA Style.Learning ResourcesRequired ReadingsFrankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society (9th ed.). Thousand Oaks, CA: Sage Publications.Chapter 12, “Regression and Correlation” (pp. 401-457) (previously read in Week 8)Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.Chapter 8, "Correlation and Regression Analysis"Chapter 11, “Editing Output” (previously read in Week 2, 3, 4, 5. 6, 7, and 8)Walden University Library. (n.d.). Course Guide and Assignment Help for RSCH 8210. Retrieved from http://academicguides.waldenu.edu/rsch8210For help with this week’s research, see this Course Guide and related weekly assignment resources.Document: Walden University: Research Design Alignment TableRequired MediaLaureate Education (Producer). (2016g). Multiple regression [Video file]. Baltimore, MD: Author.Note: The approximate length of this media piece is 7 minutes.In this media program, Dr. Matt Jones demonstrates multiple regression using the SPSS software.Accessible player --Downloads-- Download Video w/CC Download Audio Download Transcript Optional ResourcesSkill Builder: Interpreting the Results from Regression ModelsTo access these Skill Builders, navigate back to your Blackboard Course Home page, and locate “Skill Builders” in the left navigation pane. From there, click on the relevant Skill Builder link for this week. You are encouraged to click through these and all Skill Builders to gain additional practice with these concepts. Doing so will bolster your knowledge of the concepts you’re learning this week and throughout the course.
13 pages
Question Set F
Download the Excel data of E-commerce Retail Sales and follow the steps below for time series forecasting. To be able to r ...
Question Set F
Download the Excel data of E-commerce Retail Sales and follow the steps below for time series forecasting. To be able to receive full credit, you must ...
Missing Data
This week’s Learning Resources include several different ways to identify and assess the issue of missing data in your d ...
Missing Data
This week’s Learning Resources include several different ways to identify and assess the issue of missing data in your database. From your assessment and knowledge of possible ways to manipulate data, and to overcome potential challenges presented by the missing data, you will be able to analyze and reach conclusions about your analysis. It is important to recognize when and how to apply the most viable solution to the missing data. In addition, it is important to learn to recognize when your data results could be compromised by missing data.For this, you will analyze the impact of missing data on data analysis.To prepare:Review this week’s Learning Resources.Analysis of missing data. Include the following in your post:An explanation of the importance of handling missing data and skipping patterns and how missing data can affect data analysisA technique on how you may handle missing data appropriately with an explanation of why this technique worksChoose one of the variables you selected for your Scholar-Practitioner Project (select one with missing values) and report proportion of missing for that variableIndicate the possible reason for the missing values in that variable.ReferencesWang, R., Sedransk, J., & Jinn, J. H. (1992). Secondary data analysis when there are missing observations. Journal of the American Statistical Association, 7(420), 952–961. Long, J. A., Bamba, M. I., Ling, B., & Shea, J. A. (2006). Missing race/ethnicity data in Veterans Health Administration based disparities research: A systematic review. Journal of Health Care for the Poor and Underserved, 17(1), 128–140.Langkamp, D. L., Lehman, A., & Lemeshow, S. (2010). Techniques for handling missing data in secondary analyses of large surveys. Academic Pediatrics, 10(3), 205–210.
CSU Mod 2 Coefficient of Variation & Standard Deviation Research
The coefficient of variation and the standard deviation are two measures of variability or dispersion among data values. P ...
CSU Mod 2 Coefficient of Variation & Standard Deviation Research
The coefficient of variation and the standard deviation are two measures of variability or dispersion among data values. Provide two different sets of ten data points each as examples. Calculate the standard deviation and coefficient of variation for each data set, being sure to attach your Excel file to show your work. Explain which of the two mentioned measures can more accurately specify which of these two data sets has more variability or dispersion in their data values and why.Research the method behind the Excel function “QUARTILE.EXC” for calculating quartiles for a given data set. Summarize this method in your own words and discuss how it differs from the method presented in the textbook and lecture.Your document should be minimum 400 words. Please have credible references.
5 pages
Deliverable 4 Questions Final Copy
1. Describe the 8 steps in the process for hypothesis testing. Explain the decision criteria for rejecting the null hypoth ...
Deliverable 4 Questions Final Copy
1. Describe the 8 steps in the process for hypothesis testing. Explain the decision criteria for rejecting the null hypothesis for both the p-value ...
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