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8C2 * 13C2 = (8*7/2)* (13*12/2) = 28*78 =2184
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Week 3 Assignment: Benchmark - Simulation and Risk Analysis Case Study
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University of Mary Washington The Arithmetic Mean and Data Manipulation Questions
Please download the required CSV data file here:https://drive.google.com/file/d/1R63J3Z2LtnIsdnhqdBNt-4lxEzTOxpmI/view?usp ...
University of Mary Washington The Arithmetic Mean and Data Manipulation Questions
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SNHU Housing Price Prediction Model Project
Overview
Recall that samples are used to generate a statistic, which businesses use to estimate the population parameter. ...
SNHU Housing Price Prediction Model Project
Overview
Recall that samples are used to generate a statistic, which businesses use to estimate the population parameter. You have learned how to take samples from populations and use them to produce statistics. For two quantitative variables, businesses can use scatterplots and the correlation coefficient to explore a potential linear relationship. Furthermore, they can quantify the relationship in a regression equation.
Prompt
This assignment picks up where the Module Two assignment left off and will use components of that assignment as a foundation.
You have submitted your initial analysis to the sales team at D.M. Pan Real Estate Company. You will continue your analysis of the provided Real Estate Data spreadsheet using your selected region to complete your analysis. You may refer back to the initial report you developed in the Module Two Assignment Template to continue the work. This document and the National Statistics and Graphs spreadsheet will support your work on the assignment.
Note: In the report you prepare for the sales team, the dependent, or response, variable (y) should be the listing price and the independent, or predictor, variable (x) should be the square feet.
Using the Module Three Assignment Template, specifically address the following:
Regression Equation: Provide the regression equation for the line of best fit using the scatterplot from the Module Two assignment.
Determine r: Determine r and what it means. (What is the relationship between the variables?)
Determine the strength of the correlation (weak, moderate, or strong).
Discuss how you determine the direction of the association between the two variables.
Is there a positive or negative association?
What do you see as the direction of the correlation?
Examine the Slope and Intercepts: Examine the slopeb1{"version":"1.1","math":"b1"} and intercept b0{"version":"1.1","math":"b0"}.
Draw conclusions from the slope and intercept in the context of this problem.
Does the intercept make sense based on your observation of the line of best fit?
Determine the value of the land only.
Note: You can assume, when the square footage of the house is zero, that the price is the value of just the land. This happens when x=0, which is the y-intercept. Does this value make sense in context?
Determine the R-squared Coefficient: Determine the R-squared value.
Discuss what R-squared means in the context of this analysis.
Conclusions: Reflect on the Relationship: Reflect on the relationship between square feet and sales price by answering the following questions:
Is the square footage for homes in your selected region different than for homes overall in the United States?
For every 100 square feet, how much does the price go up (i.e., can you use slope to help identify price changes)?
What square footage range would the graph be best used for?
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Questions to Be Graded: Exercises 14,19, 29, and 35
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Week 3 Assignment: Benchmark - Simulation and Risk Analysis Case Study
The purpose of this assignment is to use analytics techniques to analyze a case problem.Part 1Read Case Study Case 15.2 � ...
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The purpose of this assignment is to use analytics techniques to analyze a case problem.Part 1Read Case Study Case 15.2 “Ebony Bath Soap” attached BELOW, and then complete the following items.For Questions 1 and 2 of the case, use the Palisade DecisionTools Excel software to set up a simulation model and run a simulation with 500 trials for the case. Ensure that all Palisade software output is included in your files and that only one Excel file is open when running a simulation. Use the "Topic 3 Case Study Template" file as a starting point. Hint: The RiskSimtable function was be helpful for running the simulations.Respond to Question 3 as written in the problem. Ignore the confidence interval portion of the question.Respond to Question 4 as written in the problem.To receive full credit on the assignment, complete the following.Ensure that the Palisade software output is included with your submission.Ensure that Excel files include the associated cell functions and/or formulas if functions and/or formulas are used.Include a written response to all narrative questions presented in the problem by placing it in the associated Excel file.Include screenshots of all simulation distribution results for output variables.Place each problem in its own Excel file. Ensure that your first and last name are in your Excel file names.Part 2In a 500-750-word summary to company management, address the following. Include relevant charts and graphs within your summary, as needed.Describe the case specific business requirements and how they can be communicated across all levels of the organization.Based on the simulation results, discuss the Annual Cost output statistical distributions. Assume that your audience as minimal background in statistics.Discuss which Annual Cost output probability distribution has the most dispersion, and explain why this is so. Explain the descriptive, predictive, and prescriptive analytics that have been used to formulate the solutions to the business needs.Based on the Annual Cost output statistical distributions and other information gleaned from your analysis, discuss the specific prescribed course of action you would recommend to company management and justify your recommendations. Include discussion of how the proposed analytics solutions can optimize organizational performance and effectiveness.
University of Mary Washington The Arithmetic Mean and Data Manipulation Questions
Please download the required CSV data file here:https://drive.google.com/file/d/1R63J3Z2LtnIsdnhqdBNt-4lxEzTOxpmI/view?usp ...
University of Mary Washington The Arithmetic Mean and Data Manipulation Questions
Please download the required CSV data file here:https://drive.google.com/file/d/1R63J3Z2LtnIsdnhqdBNt-4lxEzTOxpmI/view?usp=sharing (Links to an external site.)This assignment will focus on using some of the techniques we have seen over the past three weeks for manipulating data in R. For this assignment we will be working with a dataset consisting of demographics together with weekly religious service attendance for 5000 individuals. Most of the variable names are self-explanatory, but the “Weekly Attendance” column shows a value of “1” for those who report attending religious services weekly and “0” for those who don’t. You will read this file into R and answer a few questions that will require you to apply data transforms for finding the answer.Important Formatting Instructions: Please round all answers to the nearest whole number. There should be no decimals or commas, only integers. Here some examples of what to do (good examples) and what NOT to do (bad examples):Good Examples (enter examples like these): 5, 2, 22, 11, 128, 228000Bad Examples (don’t do this!): 5.31, 2.0, 22.000, 11.88231, 128.0, 228,000INTEGRITY STATEMENTYou must work on this entirely alone without consulting with any other student. You may certainly use your notes and any class materials as well as outside R resources, but you may NOT ask others for help or seek the answers on the Internet or from any other source. This must be entirely your own work. Additionally, you may NOT discuss these answers or in any way make them public. The Honor Code is in full effect!HOW TO SUBMITUse R to answer the questions below. It is recommended to work the answers out first, then log into the website below to enter your answers. You will need to enter them all in one sitting. Please MAKE SURE to follow the formatting instructions so you don’t needlessly lose points.Once you are ready, you may log on with your NetID and enter your answers HERE (Links to an external site.)QUESTIONS1. What is the mean number of years of education?2. What is the median age?3. How many males are in this dataset?4. How many females are in this dataset?5. How many married females are in this dataset?6. How many unmarried males attend services weekly in this dataset?7. What is the median income of those who attend services weekly?8. What is the median income of those who DO NOT attend services weekly?For the next 3 questions, add a new column called “HigherEd” that provides a label based on years of education according to the following rules:Educ < 12: “None”12 <= Educ < 16: “HighSchool”16 <= Educ < 17: “College”17 <= Educ < 19: “Masters”Educ >= 19: “Doctorate”9. What is the median income for those with HigherEd = “College”?10. How many females with HigherEd = “Masters” in this data?11. How many individuals who hold a doctorate attend weekly religious services?
SNHU Housing Price Prediction Model Project
Overview
Recall that samples are used to generate a statistic, which businesses use to estimate the population parameter. ...
SNHU Housing Price Prediction Model Project
Overview
Recall that samples are used to generate a statistic, which businesses use to estimate the population parameter. You have learned how to take samples from populations and use them to produce statistics. For two quantitative variables, businesses can use scatterplots and the correlation coefficient to explore a potential linear relationship. Furthermore, they can quantify the relationship in a regression equation.
Prompt
This assignment picks up where the Module Two assignment left off and will use components of that assignment as a foundation.
You have submitted your initial analysis to the sales team at D.M. Pan Real Estate Company. You will continue your analysis of the provided Real Estate Data spreadsheet using your selected region to complete your analysis. You may refer back to the initial report you developed in the Module Two Assignment Template to continue the work. This document and the National Statistics and Graphs spreadsheet will support your work on the assignment.
Note: In the report you prepare for the sales team, the dependent, or response, variable (y) should be the listing price and the independent, or predictor, variable (x) should be the square feet.
Using the Module Three Assignment Template, specifically address the following:
Regression Equation: Provide the regression equation for the line of best fit using the scatterplot from the Module Two assignment.
Determine r: Determine r and what it means. (What is the relationship between the variables?)
Determine the strength of the correlation (weak, moderate, or strong).
Discuss how you determine the direction of the association between the two variables.
Is there a positive or negative association?
What do you see as the direction of the correlation?
Examine the Slope and Intercepts: Examine the slopeb1{"version":"1.1","math":"b1"} and intercept b0{"version":"1.1","math":"b0"}.
Draw conclusions from the slope and intercept in the context of this problem.
Does the intercept make sense based on your observation of the line of best fit?
Determine the value of the land only.
Note: You can assume, when the square footage of the house is zero, that the price is the value of just the land. This happens when x=0, which is the y-intercept. Does this value make sense in context?
Determine the R-squared Coefficient: Determine the R-squared value.
Discuss what R-squared means in the context of this analysis.
Conclusions: Reflect on the Relationship: Reflect on the relationship between square feet and sales price by answering the following questions:
Is the square footage for homes in your selected region different than for homes overall in the United States?
For every 100 square feet, how much does the price go up (i.e., can you use slope to help identify price changes)?
What square footage range would the graph be best used for?
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