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MAT 240 Southern New Hampshire University Housing Price Prediction Worksheet
CompetenciesIn this project, you will demonstrate your mastery of the following competencies:Apply statistical techniques ...
MAT 240 Southern New Hampshire University Housing Price Prediction Worksheet
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 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 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 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 houses.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 DataUse this data for input in your project report.Tutorial: Downloading Office 365 ProgramsUse this tutorial for support with Office 365 programs.
discussion board
Step 1: Respond to the following:Imagine you are writing exam questions for an algebra course. You want to write questions ...
discussion board
Step 1: Respond to the following:Imagine you are writing exam questions for an algebra course. You want to write questions that include finding the zeros of polynomials. To balance the difficulty level of the test’s questions, you decide to include two different types of questions, as described here:Question #1: A polynomial of degree at least 3 where all the zeros are positive whole numbersQuestion #2: A polynomial of degree at least 3 where one or more of the roots are fractionsFind two polynomials for the two described questions. Explain how you know each question satisfies the requirements stated. What approach did you use to find these polynomials?Step 2: Then, respond to at least two other classmates' posts, comparing your concepts with theirs. Once again, use any personal experience if appropriate to help support or debate other students' posts. If differences of opinion occur, students should debate the issues and provide examples to support opinions.*Be sure to cite any outside sources in APA format
Computation by hand, statistics homework help
Assignment: Computation by Hand Answer question 1 using data in table 1 below. Table 1: Survival Status ...
Computation by hand, statistics homework help
Assignment: Computation by Hand Answer question 1 using data in table 1 below. Table 1: Survival Status Donor’s Sex Alive Dead Total Female 52 4 56 Male 110 27 137 Total 162 31 193 Compute the simple odds ratio of the association of donor’s sex and survival status of the infant. Be sure to answer all four parts to this question (a, b, c, and d), including manual calculation of the chi-square value a. Manually calculate a simple odds ratio to test the hypothesis of no association between donor’s sex and the survival status of the infant, without the inclusion of the variable severity using a 2 x 2 table for sex and survival b. Manually calculate the confidence interval associated with that odds ratio using the appropriate formula c. Manually compute the Chi Square test statistic for this table d. Interpret the results. Include an interpretation of the odds ratio, the confidence interval, and the Chi Square test statistic in your Table 2: Survival Status Disease Severity Donor’s Sex Alive Dead Total None Female 14 1 15 Male 21 2 23 Mild Female 17 1 18 Male 40 2 42 Moderate Female 15 1 16 Male 33 6 39 Severe Female 6 1 7 Male 16 17 33 Total 162 31 193 Using data in table 2, compute the common odds ratio of the association between donor’s sex and the survival status of the infant, after controlling for severity a. Manually calculate a common odds ratio to test the hypothesis of no association between donor’s sex and the survival status of the infant, after the inclusion of the variable severity using the common odds ratio b. Interpret the results. How does the common odds ratio differ from the simple odds ratio computed in part 1? What effect might it have on your decision from part 1 to reject or fail to reject the null hypothesis? c. Why is it important to know the effect of severity on the association of gender and survival? Perform a simple logistic regression using SPSS and the Week 6 Dataset (SPSS document). Answer the following questions based on your SPSS output a. Are the results of the simple logistic regression similar to or different from the results of the simple odds ratio? b. How are they similar or different? Include output from SPSS and an interpretation of the OR and confidence intervals in your response c. What can you do using logistic regression to duplicate the results from part 2 of this application (the use of CMH for common odds) Resources Daniel, WW & Cross, CL. (2013). Biostatistics: A Foundation for Analysis in the Health Sciences. Hoboken, NJ: Wiley. Chapter 11, “ Regression Analysis: Some Additional Techniques” ( pp. 539 –599) Chapter 12, “Chi Square Distributions” ( pp. 600 –669)
MTH 154 WVNCC Using a Dice to Model the Spread of A Disease Math Questions
Please I need help with this assignment. I also need the step explanation.Below is the attachment
MTH 154 WVNCC Using a Dice to Model the Spread of A Disease Math Questions
Please I need help with this assignment. I also need the step explanation.Below is the attachment
South University Slope and The Y Intercept Graphing Questions
1. Given that y = 4x - 1. What is the slope and the y-intercept? Give a table of four ordered pairs for this relation.2. G ...
South University Slope and The Y Intercept Graphing Questions
1. Given that y = 4x - 1. What is the slope and the y-intercept? Give a table of four ordered pairs for this relation.2. Given that y = -2x + 5. What is the slope and the y-intercept? Give a table of four ordered pairs for this relation.3. Given that y = -25x + 3.Explain what the slope says about the relation between x and y. Give a table of four ordered pairs for this relation.4. Given y = 12x.Explain what the slope says about the relation between x and y. Give a table of four ordered pairs for this relation.
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MAT 240 Southern New Hampshire University Housing Price Prediction Worksheet
CompetenciesIn this project, you will demonstrate your mastery of the following competencies:Apply statistical techniques ...
MAT 240 Southern New Hampshire University Housing Price Prediction Worksheet
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 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 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 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 houses.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 DataUse this data for input in your project report.Tutorial: Downloading Office 365 ProgramsUse this tutorial for support with Office 365 programs.
discussion board
Step 1: Respond to the following:Imagine you are writing exam questions for an algebra course. You want to write questions ...
discussion board
Step 1: Respond to the following:Imagine you are writing exam questions for an algebra course. You want to write questions that include finding the zeros of polynomials. To balance the difficulty level of the test’s questions, you decide to include two different types of questions, as described here:Question #1: A polynomial of degree at least 3 where all the zeros are positive whole numbersQuestion #2: A polynomial of degree at least 3 where one or more of the roots are fractionsFind two polynomials for the two described questions. Explain how you know each question satisfies the requirements stated. What approach did you use to find these polynomials?Step 2: Then, respond to at least two other classmates' posts, comparing your concepts with theirs. Once again, use any personal experience if appropriate to help support or debate other students' posts. If differences of opinion occur, students should debate the issues and provide examples to support opinions.*Be sure to cite any outside sources in APA format
Computation by hand, statistics homework help
Assignment: Computation by Hand Answer question 1 using data in table 1 below. Table 1: Survival Status ...
Computation by hand, statistics homework help
Assignment: Computation by Hand Answer question 1 using data in table 1 below. Table 1: Survival Status Donor’s Sex Alive Dead Total Female 52 4 56 Male 110 27 137 Total 162 31 193 Compute the simple odds ratio of the association of donor’s sex and survival status of the infant. Be sure to answer all four parts to this question (a, b, c, and d), including manual calculation of the chi-square value a. Manually calculate a simple odds ratio to test the hypothesis of no association between donor’s sex and the survival status of the infant, without the inclusion of the variable severity using a 2 x 2 table for sex and survival b. Manually calculate the confidence interval associated with that odds ratio using the appropriate formula c. Manually compute the Chi Square test statistic for this table d. Interpret the results. Include an interpretation of the odds ratio, the confidence interval, and the Chi Square test statistic in your Table 2: Survival Status Disease Severity Donor’s Sex Alive Dead Total None Female 14 1 15 Male 21 2 23 Mild Female 17 1 18 Male 40 2 42 Moderate Female 15 1 16 Male 33 6 39 Severe Female 6 1 7 Male 16 17 33 Total 162 31 193 Using data in table 2, compute the common odds ratio of the association between donor’s sex and the survival status of the infant, after controlling for severity a. Manually calculate a common odds ratio to test the hypothesis of no association between donor’s sex and the survival status of the infant, after the inclusion of the variable severity using the common odds ratio b. Interpret the results. How does the common odds ratio differ from the simple odds ratio computed in part 1? What effect might it have on your decision from part 1 to reject or fail to reject the null hypothesis? c. Why is it important to know the effect of severity on the association of gender and survival? Perform a simple logistic regression using SPSS and the Week 6 Dataset (SPSS document). Answer the following questions based on your SPSS output a. Are the results of the simple logistic regression similar to or different from the results of the simple odds ratio? b. How are they similar or different? Include output from SPSS and an interpretation of the OR and confidence intervals in your response c. What can you do using logistic regression to duplicate the results from part 2 of this application (the use of CMH for common odds) Resources Daniel, WW & Cross, CL. (2013). Biostatistics: A Foundation for Analysis in the Health Sciences. Hoboken, NJ: Wiley. Chapter 11, “ Regression Analysis: Some Additional Techniques” ( pp. 539 –599) Chapter 12, “Chi Square Distributions” ( pp. 600 –669)
MTH 154 WVNCC Using a Dice to Model the Spread of A Disease Math Questions
Please I need help with this assignment. I also need the step explanation.Below is the attachment
MTH 154 WVNCC Using a Dice to Model the Spread of A Disease Math Questions
Please I need help with this assignment. I also need the step explanation.Below is the attachment
South University Slope and The Y Intercept Graphing Questions
1. Given that y = 4x - 1. What is the slope and the y-intercept? Give a table of four ordered pairs for this relation.2. G ...
South University Slope and The Y Intercept Graphing Questions
1. Given that y = 4x - 1. What is the slope and the y-intercept? Give a table of four ordered pairs for this relation.2. Given that y = -2x + 5. What is the slope and the y-intercept? Give a table of four ordered pairs for this relation.3. Given that y = -25x + 3.Explain what the slope says about the relation between x and y. Give a table of four ordered pairs for this relation.4. Given y = 12x.Explain what the slope says about the relation between x and y. Give a table of four ordered pairs for this relation.
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