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volume= base area * height of the cylinder
3.142*r^2*h.................................................................................................................................
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Ma105 Statistics Chapter 9 Problem Post
1) Two math teachers each believe that their own very large class is doing better than the other class. The teachers decid ...
Ma105 Statistics Chapter 9 Problem Post
1) Two math teachers each believe that their own very large class is doing better than the other class. The teachers decide to determine whose class ...
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Please do a comparable valuation of hertz using the form attached. You must use our form. Also, please provide a separate ...
valuation of Hertz
Please do a comparable valuation of hertz using the form attached. You must use our form. Also, please provide a separate word document with your commentary. The commentary is very important. It can and should draw from any information available that you believe is important.and its competitor companies are Uber, Lyft
MAT 240 Southern New Hampshire University Real Estate Company Discussion
CompetenciesIn this project, you will demonstrate your mastery of the following competencies:Apply statistical techniques ...
MAT 240 Southern New Hampshire University Real Estate Company Discussion
CompetenciesIn this project, you will demonstrate your mastery of the following competencies:Apply statistical techniques to address research problemsPerform regression analysis to address an authentic problemOverviewThe purpose of this project is to have you complete all of the steps
of a real-world linear regression research project starting with
developing a research question, then completing a comprehensive
statistical analysis, and ending with summarizing your research
conclusions.ScenarioYou have been hired by the D. M. Pan National Real Estate Company to
develop a model to predict median housing prices for homes sold in 2019.
The CEO of D. M. Pan wants to use this information to help their real
estate agents better determine the use of square footage as a benchmark
for listing prices on homes. Your task is to provide a report predicting
the median housing prices based square footage. To complete this task,
use the provided real estate data set for all U.S. home sales as well as
national descriptive statistics and graphs provided.DirectionsUsing the Project One Template located in the What to Submit section,
generate a report including your tables and graphs to determine if the
square footage of a house is a good indicator for what the listing price
should be. Reference the National Statistics and Graphs document for
national comparisons and the Real Estate County Data spreadsheet (both
found in the Supporting Materials section) for your statistical
analysis.Note: Present your data in a clearly labeled table and using clearly labeled graphs.Specifically, include the following in your report:IntroductionDescribe the report: Give a brief description of the purpose of your report.
Define the question your report is trying to answer.Explain when using linear regression is most appropriate.
When using linear regression, what would you expect the scatterplot to look like?
Explain the difference between response and predictor variables in a linear regression to justify the selection of variables.
Data CollectionSampling the data: Select a random sample of 50 counties.
Identify your response and predictor variables.
Scatterplot: Create a scatterplot of your response and predictor variables to ensure they are appropriate for developing a linear model.Data AnalysisHistogram: For your two variables, create histograms.Summary statistics: For your two variables, create a table to show the mean, median, and standard deviation.Interpret the graphs and statistics:
Based on your graphs and sample statistics, interpret the center,
spread, shape, and any unusual characteristic (outliers, gaps, etc.) for
the two variables.Compare and contrast the shape, center, spread, and any unusual
characteristic for your sample of house sales with the national
population. Is your sample representative of national housing market
sales?
Develop Your Regression ModelScatterplot: Provide a graph of the scatterplot of the data with a line of best fit.
Explain if a regression model is appropriate to develop based on your scatterplot.
Discuss associations: Based on the scatterplot, discuss the association (direction, strength, form) in the context of your model.
Identify any possible outliers or influential points and discuss their effect on the correlation.Discuss keeping or removing outlier data points and what impact your decision would have on your model.
Find r: Find the correlation coefficient (r).
Explain how the r value you calculated supports what you noticed in your scatterplot.
Determine the Line of Best Fit. Clearly define your variables. Find and interpret the regression equation. Assess the strength of the model.Regression equation: Write the regression equation (i.e., line of best fit) and clearly define your variables. Interpret regression equation: Interpret the slope and intercept in context.Strength of the equation: Provide and interpret R-squared.
Determine the strength of the linear regression equation you developed.
Use regression equation to make predictions: Use your regression equation to predict how much you should list your home for based on the square footage of your home.ConclusionsSummarize findings: In one paragraph, summarize
your findings in clear and concise plain language for the CEO to
understand. Summarize your results.
Did you see the results you expected, or was anything different from your expectations or experiences?
What changes could support different results, or help to solve a different problem?Provide at least one question that would be interesting for follow-up research.
What to SubmitTo complete this project, you must submit the following:Project One Template: Use this template to structure your report, and submit the finished version as a Word document.Supporting MaterialsThe following resources may help support your work on the project:Document: National Statistics and GraphsUse this data for input in your project report.Spreadsheet: Real Estate County DataUse this data for input in your project report.Tutorial: Downloading Office 365 ProgramsUse this tutorial for support with Office 365 programs.
the perspectives of culturally relevant teaching
In this assignment, you will choose one of the Algebra tasks given below and use a rubric to analyze the task. This rubric ...
the perspectives of culturally relevant teaching
In this assignment, you will choose one of the Algebra tasks given below and use a rubric to analyze the task. This rubric is the result of a framework connecting higher level tasks with the perspectives of culturally relevant teaching, thus refining the descriptions of two of the categories presented by Smith and Stein as (a)procedures with connections to concepts, meaning and understanding of mathematics, culture and community, and (b) doing mathematics for the purpose of becoming empowered intellectually, culturally, politically and socially. These two renamed classifications are given for the purpose of having teachers of mathematicsrethink the extent to which selected mathematics tasks challenge students to ask relevant questions of themselves and the world around them (Matthews, Jones, and Parker, 2013).
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Most Popular Content
2 pages
Ma105 Statistics Chapter 9 Problem Post
1) Two math teachers each believe that their own very large class is doing better than the other class. The teachers decid ...
Ma105 Statistics Chapter 9 Problem Post
1) Two math teachers each believe that their own very large class is doing better than the other class. The teachers decide to determine whose class ...
valuation of Hertz
Please do a comparable valuation of hertz using the form attached. You must use our form. Also, please provide a separate ...
valuation of Hertz
Please do a comparable valuation of hertz using the form attached. You must use our form. Also, please provide a separate word document with your commentary. The commentary is very important. It can and should draw from any information available that you believe is important.and its competitor companies are Uber, Lyft
MAT 240 Southern New Hampshire University Real Estate Company Discussion
CompetenciesIn this project, you will demonstrate your mastery of the following competencies:Apply statistical techniques ...
MAT 240 Southern New Hampshire University Real Estate Company Discussion
CompetenciesIn this project, you will demonstrate your mastery of the following competencies:Apply statistical techniques to address research problemsPerform regression analysis to address an authentic problemOverviewThe purpose of this project is to have you complete all of the steps
of a real-world linear regression research project starting with
developing a research question, then completing a comprehensive
statistical analysis, and ending with summarizing your research
conclusions.ScenarioYou have been hired by the D. M. Pan National Real Estate Company to
develop a model to predict median housing prices for homes sold in 2019.
The CEO of D. M. Pan wants to use this information to help their real
estate agents better determine the use of square footage as a benchmark
for listing prices on homes. Your task is to provide a report predicting
the median housing prices based square footage. To complete this task,
use the provided real estate data set for all U.S. home sales as well as
national descriptive statistics and graphs provided.DirectionsUsing the Project One Template located in the What to Submit section,
generate a report including your tables and graphs to determine if the
square footage of a house is a good indicator for what the listing price
should be. Reference the National Statistics and Graphs document for
national comparisons and the Real Estate County Data spreadsheet (both
found in the Supporting Materials section) for your statistical
analysis.Note: Present your data in a clearly labeled table and using clearly labeled graphs.Specifically, include the following in your report:IntroductionDescribe the report: Give a brief description of the purpose of your report.
Define the question your report is trying to answer.Explain when using linear regression is most appropriate.
When using linear regression, what would you expect the scatterplot to look like?
Explain the difference between response and predictor variables in a linear regression to justify the selection of variables.
Data CollectionSampling the data: Select a random sample of 50 counties.
Identify your response and predictor variables.
Scatterplot: Create a scatterplot of your response and predictor variables to ensure they are appropriate for developing a linear model.Data AnalysisHistogram: For your two variables, create histograms.Summary statistics: For your two variables, create a table to show the mean, median, and standard deviation.Interpret the graphs and statistics:
Based on your graphs and sample statistics, interpret the center,
spread, shape, and any unusual characteristic (outliers, gaps, etc.) for
the two variables.Compare and contrast the shape, center, spread, and any unusual
characteristic for your sample of house sales with the national
population. Is your sample representative of national housing market
sales?
Develop Your Regression ModelScatterplot: Provide a graph of the scatterplot of the data with a line of best fit.
Explain if a regression model is appropriate to develop based on your scatterplot.
Discuss associations: Based on the scatterplot, discuss the association (direction, strength, form) in the context of your model.
Identify any possible outliers or influential points and discuss their effect on the correlation.Discuss keeping or removing outlier data points and what impact your decision would have on your model.
Find r: Find the correlation coefficient (r).
Explain how the r value you calculated supports what you noticed in your scatterplot.
Determine the Line of Best Fit. Clearly define your variables. Find and interpret the regression equation. Assess the strength of the model.Regression equation: Write the regression equation (i.e., line of best fit) and clearly define your variables. Interpret regression equation: Interpret the slope and intercept in context.Strength of the equation: Provide and interpret R-squared.
Determine the strength of the linear regression equation you developed.
Use regression equation to make predictions: Use your regression equation to predict how much you should list your home for based on the square footage of your home.ConclusionsSummarize findings: In one paragraph, summarize
your findings in clear and concise plain language for the CEO to
understand. Summarize your results.
Did you see the results you expected, or was anything different from your expectations or experiences?
What changes could support different results, or help to solve a different problem?Provide at least one question that would be interesting for follow-up research.
What to SubmitTo complete this project, you must submit the following:Project One Template: Use this template to structure your report, and submit the finished version as a Word document.Supporting MaterialsThe following resources may help support your work on the project:Document: National Statistics and GraphsUse this data for input in your project report.Spreadsheet: Real Estate County DataUse this data for input in your project report.Tutorial: Downloading Office 365 ProgramsUse this tutorial for support with Office 365 programs.
the perspectives of culturally relevant teaching
In this assignment, you will choose one of the Algebra tasks given below and use a rubric to analyze the task. This rubric ...
the perspectives of culturally relevant teaching
In this assignment, you will choose one of the Algebra tasks given below and use a rubric to analyze the task. This rubric is the result of a framework connecting higher level tasks with the perspectives of culturally relevant teaching, thus refining the descriptions of two of the categories presented by Smith and Stein as (a)procedures with connections to concepts, meaning and understanding of mathematics, culture and community, and (b) doing mathematics for the purpose of becoming empowered intellectually, culturally, politically and socially. These two renamed classifications are given for the purpose of having teachers of mathematicsrethink the extent to which selected mathematics tasks challenge students to ask relevant questions of themselves and the world around them (Matthews, Jones, and Parker, 2013).
8 pages
Gather And Analyze Data
1. 1. How often do you find your job to be stressful? 3. How frequently do you require extra patience or strength at work?
Gather And Analyze Data
1. 1. How often do you find your job to be stressful? 3. How frequently do you require extra patience or strength at work?
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