Apply statistical techniques to address research problems

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Scenario
You 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.

Directions
Using 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 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:

Introduction
Describe 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 predictor (x) and response (y) variables in a linear regression to justify the selection of variables.
Data Collection
Sampling the data: Select a random sample of 50 houses. Describe how you obtained your sample data (provide Excel formulas as appropriate).
Identify your predictor and response variables.
Scatterplot: Create a scatterplot of your predictor and response variables to ensure they are appropriate for developing a linear model.
Data Analysis
Histogram: Create a histogram for each of the two variables.
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 house sales and square footage.
Compare and contrast the center, shape, spread, and any unusual characteristic for your sample of house sales with the national population (under Supporting Materials, see the National Summary Statistics and Graphs House Listing Price by Region PDF). Determine whether your sample is representative of national housing market sales.
Develop Your Regression Model
Scatterplot: Provide a scatterplot of the variables with a line of best fit and regression equation.
Based on your scatterplot, explain if a regression model is appropriate.
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.
Calculate r: Calculate 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. For example, answer the questions: what does the slope represent in this situation? What does the intercept represent? Revisit the Scenario above.
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 assumed square footage of your home at 1500 square feet.
Conclusions
Summarize 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.
You can use the following tutorial that is specifically about this assignment. Make sure to check the assignment prompt for specific numbers used for national statistics. The videos may use different national statistics. You should use the national statistics posted with this assignment.

MAT-240 Module 4 Project One Video

Sample Solution

To start, preventing cultural heritage to come into the hands of Islamic State could cause economic setbacks for IS. IS makes profits through several ways, like taxes and fees from the people under their regime, natural resources like oil, foreign donations, but also from selling antiquities they obtained from cultural heritage sites (Heißner et al. 2017, 7). In Turkey alone, which shares a border with IS territory, the authorities caught 6,800 objects from  2011 to 2016 that came from cultural heritage sites and where being smuggles across the border to be sold (Myers and Kulish, 2016). Estimates show that the profits IS makes from selling looted antiquities vary millions to hundreds of millions of dollars on a yearly base (Vlasic and Turku 2016, 1177). Also, in “The Islamic State’s symbolic war: Da’esh’s socially mediated terrorism as a threat to cultural heritage” Smith et al. state that internal profits, like looted antiquities, made by IS are essential for the continuation and survival of IS, as they can be used for the costs IS makes (Smith et al. 2016, 179-80). As IS makes profits from selling antiquities obtained from cultural heritage sites, preventing IS to lay hand on these cultural heritage sites will thus cause a financial setback for IS, affecting the chances of IS surviving. Furthermore, data found in a collaborative research in 2017 conducted by EY and the International Centre for the Study of Radicalisation, which is part of King’s College London, shows that although the share of antiquities is at the bottom of profit shares made by IS, with profits made from oil leading the list (Heißner et al. 2017, 8), the financials of IS are already in decline (Heißner et al. 2017, 10), which suggests that any profit made, even if it is not that much, is very valuable for IS. It was estimated that the overall income of IS decreased by approximately 50 percent in just two years from 1.9 billion dollars in 2014 to 870 million dollars in 2016 (Heißner et al. 2017, 10). This was mainly because of loss of in territory which resulted in less natural resources to sell, and fewer people and businesses to receive taxes from. Also, some actions taken by the Global Coalition to reduce Islamic State’s financial income have had some influence like actions taken at the border of IS’s territory to counter smuggling and Operation Tidal Wave II which was launched in 2015 which permitted attacking oil transportation lines and cash depots (Heißner et al. 2017, 12). Furthermore, IS has so far not succeeded to come up with new sources of funding that would replace the losses that have been made lately (Heißner et al. 2017, 5). The study suggests that if IS continues down the same path, their ‘”business model”’ will not last for long (Heißner et al. 2017, 3).  main topic sentence

Another argument supporting the claim that preventing cultural heritage sites to fall into the hands of IS will help in the fight against them is that IS will lose a way to express their power and ideology on a global scale and recruit new members. Besides the fact that they do this because The emergence of social media brought a new way of terrorism into being. In “The Islamic State’s symbolic war: Da’esh’s socia

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