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Week 4 MIS-690 Model Building Assignment
DQ1What are the general steps taken to build an analytics model? Please
provide examples.DQ 2When building a model, ho ...
Week 4 MIS-690 Model Building Assignment
DQ1What are the general steps taken to build an analytics model? Please
provide examples.DQ 2When building a model, how do you know if it is the correct one? Are
you able to trust the model that you built in order to apply the data
correctly to solve a company's problem?AssignmentYou will need to build a model that will solve the problem that you
have identified. Use one or more of the following software
applications: IBM SPSS Modeler, SPSS Statistics, Excel, Tableau, or R.Write a 500-750 word paper describing your model. It will include
the following: What models did you build? Why did you choose this
model(s)? Be sure that this model specifically ties back to the
business problem you created for the Topic 1 assignment.
What variables did you include or leave out and why?
Provide specific screenshots from the modeling software in your
paper. Provide the raw software files that you used for this assignment
(IBM SPSS Modeler, SPSS Statistics, Excel, Tableau, or R). If R was
used, provide a *.txt file of all the commands used.Prepare this assignment according to the guidelines found in the APA
Style Guide, located in the Student Success Center. An abstract is not required.This assignment uses a rubric. Please review the rubric prior to
beginning the assignment to become familiar with the expectations for
successful completion.
STA 201 Thomas Edison State University Variables in The Class Dataset Excel Task
To complete the final project, follow these steps:
Devise two research questions based on the variables in the class da ...
STA 201 Thomas Edison State University Variables in The Class Dataset Excel Task
To complete the final project, follow these steps:
Devise two research questions based on the variables in the class dataset.
Identify the variables to be utilized. One should be categorical (which may be created from a continuous variable, i.e., variable months enrolled at TESU; Categories: less than one year and one or more years) and two should be continuous variables.
Use descriptive statistics to describe the variables both numerically and graphically.
Devise hypotheses for both research questions.
Identify the appropriate statistical tests using alpha=0.05.
Perform the statistical tests.
Write up the results.
Variables in the class dataset:
TESU school in which you are enrolled
Arts and Sciences
Applied Science and Technology
Business and Management
Nursing
Public Service
Months enrolled at TESU
Number from 0 to 48 (if over 48, enter 49)
Birthday month
Average distance to your place of work (in whole miles)
Height (in whole inches)
Foot size (in whole inches)
Hand size (measured from base of palm to longest finger; in whole inches)
Typical amount of sleep per night (in minutes)
Typical amount of time doing homework per day for classes at TESU (in minutes)
5 pages
Statistical Documentation
Complete your work in this document in black type. Leave the existing document in the blue type it is currently in and do ...
Statistical Documentation
Complete your work in this document in black type. Leave the existing document in the blue type it is currently in and do not edit the document except ...
RSCH 8210 Walden University Week 6 Research Design and t Tests Discussion
Discussion: Research Design and t Tests: How Are They Connected?Whether in a scholarly or practitioner setting, good resea ...
RSCH 8210 Walden University Week 6 Research Design and t Tests Discussion
Discussion: Research Design and t Tests: How Are They Connected?Whether in a scholarly or practitioner setting, good research and data analysis should have the benefit of peer feedback. For this Discussion, you will perform an article critique on t tests. 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 the Learning Resources and the media programs related to t tests.Search for and select a quantitative article specific to your discipline and related to t tests. Help with this task may be found in the Course guide and assignment help linked in this week’s Learning Resources. Also, you can use as a guide the Research Design Alignment Table located in this week’s Learning ResourcesBY DAY 3Write a 3- to 5-paragraph critique of the article. In your critique, include responses to the following:Which is the research design used by the authors?Why did the authors use this t test?Do you think it’s the most appropriate choice? Why or why not?Did the authors display the data?Do the results stand alone? Why or why not?Did the authors report effect size? If yes, is this meaningful?By Day 5RESPOND TO ONE OF YOUR COLLEAGUES’ POSTS AND:MAKE RECOMMENDATIONS FOR THE DESIGN CHOICE.EXPLAIN WHETHER YOU THINK THAT THIS IS THE APPROPRIATE T TEST TO USE FOR THE RESEARCH QUESTION. WHY OR WHY NOT?AS A LAY READER, WERE YOU ABLE TO UNDERSTAND THE RESULTS AND THEIR IMPLICATIONS? WHY OR WHY NOT?
MAT 240 SNHU Prediction Model for the Median Housing Price Report
CompetenciesIn this project, you will demonstrate your mastery of the following competencies:Apply statistical techniques ...
MAT 240 SNHU Prediction Model for the Median Housing Price Report
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.
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Most Popular Content
Week 4 MIS-690 Model Building Assignment
DQ1What are the general steps taken to build an analytics model? Please
provide examples.DQ 2When building a model, ho ...
Week 4 MIS-690 Model Building Assignment
DQ1What are the general steps taken to build an analytics model? Please
provide examples.DQ 2When building a model, how do you know if it is the correct one? Are
you able to trust the model that you built in order to apply the data
correctly to solve a company's problem?AssignmentYou will need to build a model that will solve the problem that you
have identified. Use one or more of the following software
applications: IBM SPSS Modeler, SPSS Statistics, Excel, Tableau, or R.Write a 500-750 word paper describing your model. It will include
the following: What models did you build? Why did you choose this
model(s)? Be sure that this model specifically ties back to the
business problem you created for the Topic 1 assignment.
What variables did you include or leave out and why?
Provide specific screenshots from the modeling software in your
paper. Provide the raw software files that you used for this assignment
(IBM SPSS Modeler, SPSS Statistics, Excel, Tableau, or R). If R was
used, provide a *.txt file of all the commands used.Prepare this assignment according to the guidelines found in the APA
Style Guide, located in the Student Success Center. An abstract is not required.This assignment uses a rubric. Please review the rubric prior to
beginning the assignment to become familiar with the expectations for
successful completion.
STA 201 Thomas Edison State University Variables in The Class Dataset Excel Task
To complete the final project, follow these steps:
Devise two research questions based on the variables in the class da ...
STA 201 Thomas Edison State University Variables in The Class Dataset Excel Task
To complete the final project, follow these steps:
Devise two research questions based on the variables in the class dataset.
Identify the variables to be utilized. One should be categorical (which may be created from a continuous variable, i.e., variable months enrolled at TESU; Categories: less than one year and one or more years) and two should be continuous variables.
Use descriptive statistics to describe the variables both numerically and graphically.
Devise hypotheses for both research questions.
Identify the appropriate statistical tests using alpha=0.05.
Perform the statistical tests.
Write up the results.
Variables in the class dataset:
TESU school in which you are enrolled
Arts and Sciences
Applied Science and Technology
Business and Management
Nursing
Public Service
Months enrolled at TESU
Number from 0 to 48 (if over 48, enter 49)
Birthday month
Average distance to your place of work (in whole miles)
Height (in whole inches)
Foot size (in whole inches)
Hand size (measured from base of palm to longest finger; in whole inches)
Typical amount of sleep per night (in minutes)
Typical amount of time doing homework per day for classes at TESU (in minutes)
5 pages
Statistical Documentation
Complete your work in this document in black type. Leave the existing document in the blue type it is currently in and do ...
Statistical Documentation
Complete your work in this document in black type. Leave the existing document in the blue type it is currently in and do not edit the document except ...
RSCH 8210 Walden University Week 6 Research Design and t Tests Discussion
Discussion: Research Design and t Tests: How Are They Connected?Whether in a scholarly or practitioner setting, good resea ...
RSCH 8210 Walden University Week 6 Research Design and t Tests Discussion
Discussion: Research Design and t Tests: How Are They Connected?Whether in a scholarly or practitioner setting, good research and data analysis should have the benefit of peer feedback. For this Discussion, you will perform an article critique on t tests. 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 the Learning Resources and the media programs related to t tests.Search for and select a quantitative article specific to your discipline and related to t tests. Help with this task may be found in the Course guide and assignment help linked in this week’s Learning Resources. Also, you can use as a guide the Research Design Alignment Table located in this week’s Learning ResourcesBY DAY 3Write a 3- to 5-paragraph critique of the article. In your critique, include responses to the following:Which is the research design used by the authors?Why did the authors use this t test?Do you think it’s the most appropriate choice? Why or why not?Did the authors display the data?Do the results stand alone? Why or why not?Did the authors report effect size? If yes, is this meaningful?By Day 5RESPOND TO ONE OF YOUR COLLEAGUES’ POSTS AND:MAKE RECOMMENDATIONS FOR THE DESIGN CHOICE.EXPLAIN WHETHER YOU THINK THAT THIS IS THE APPROPRIATE T TEST TO USE FOR THE RESEARCH QUESTION. WHY OR WHY NOT?AS A LAY READER, WERE YOU ABLE TO UNDERSTAND THE RESULTS AND THEIR IMPLICATIONS? WHY OR WHY NOT?
MAT 240 SNHU Prediction Model for the Median Housing Price Report
CompetenciesIn this project, you will demonstrate your mastery of the following competencies:Apply statistical techniques ...
MAT 240 SNHU Prediction Model for the Median Housing Price Report
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.
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