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Pages:
5 pages/≈1375 words
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Style:
APA
Subject:
Mathematics & Economics
Type:
Essay
Language:
English (U.S.)
Document:
MS Word
Date:
Total cost:
$ 21.6
Topic:

Regional vs. National Housing Price Comparison

Essay Instructions:

Competency
In this project, you will demonstrate your mastery of the following competency:
Apply statistical techniques to address research problems
Perform hypothesis testing to address an authentic problem
Overview
In this project, you will apply inference methods for means to test your hypotheses about the housing sales market for a region of the United States. You will use appropriate sampling and statistical methods.
Scenario
You have been hired by your regional real estate company to determine if your region’s housing prices and housing square footage are significantly different from those of the national market. The regional sales director has three questions that they want to see addressed in the report:
Are housing prices in your regional market lower than the national market average?
Is the square footage for homes in your region different than the average square footage for homes in the national market?
For your region, what is the range of values for the 95% confidence interval of square footage for homes in your market?
You are given a real estate data set that has houses listed for every county in the United States. In addition, you have been given national statistics and graphs that show the national averages for housing prices and square footage. Your job is to analyze the data, complete the statistical analyses, and provide a report to the regional sales director. You will do so by completing the Project Two Template located in the What to Submit area below.
Directions
Introduction
Region: Start by picking one region from the following list of regions:
West South Central, West North Central, East South Central, East North Central, Mid Atlantic
Purpose: What was the purpose of your analysis, and what is your approach?
Define a random sample and two hypotheses (means) to analyze.
Sample: Define your sample. Take a random sample of 500 observations for your region.
Describe what is included in your sample (i.e., states, region, years or months).
Questions and type of test: For your selected sample, define two hypothesis questions and the appropriate type of test hypothesis for each. Address the following for each hypothesis:
Describe the population parameter for the variable you are analyzing.
Describe your hypothesis in your own words.
Describe the inference test you will use.
Identify the test statistic.
Level of confidence: Discuss how you will use estimation and confidence intervals to help you solve the problem.
1-Tail Test
Hypothesis: Define your hypothesis.
Define the population parameter.
Write null (Ho) and alternative (Ha) hypotheses.
Specify your significance level.
Data analysis: Analyze the data and confirm assumptions have not been violated to complete this hypothesis test.
Summarize your sample data using appropriate graphical displays and summary statistics.
Provide at least one histogram of your sample data.
In a table, provide summary statistics including sample size, mean, median, and standard deviation.
Summarize your sample data, describing the center, spread, and shape in comparison to the national information.
Check the conditions.
Determine if the normal condition has been met.
Determine if there are any other conditions that you should check and whether they have been met.
Hypothesis test calculations: Complete hypothesis test calculations, providing the appropriate statistics and graphs.
Calculate the hypothesis statistics.
Determine the appropriate test statistic (t).
Calculate the probability (p value).
Interpretation: Interpret your hypothesis test results using the p value method to reject or not reject the null hypothesis.
Relate the p value and significance level.
Make the correct decision (reject or fail to reject).
Provide a conclusion in the context of your hypothesis.
2-Tail Test
Hypotheses: Define your hypothesis.
Define the population parameter.
Write null and alternative hypotheses.
State your significance level.
Data analysis: Analyze the data and confirm assumptions have not been violated to complete this hypothesis test.
Summarize your sample data using appropriate graphical displays and summary statistics.
Provide at least one histogram of your sample data.
In a table, provide summary statistics including sample size, mean, median, and standard deviation.
Summarize your sample data, describing the center, spread, and shape in comparison to the national information.
Check the assumptions.
Determine if the normal condition has been met.
Determine if there are any other conditions that should be checked on and whether they have been met.
Hypothesis test calculations: Complete hypothesis test calculations, providing the appropriate statistics and graphs.
Calculate the hypothesis statistics.
Determine the appropriate test statistic (t).
Determine the probability (p value).
Interpretation: Interpret your hypothesis test results using the p value method to reject or not reject the null hypothesis.
Relate the p value and significance level.
Make the correct decision (reject or fail to reject).
Provide a conclusion in the context of your hypothesis.
Comparison of the test results: See Question 3 from the Scenario section.
Calculate a 95% confidence interval. Show or describe your method of calculation.
Interpret a 95% confidence interval.
Final Conclusions
Summarize your findings: Refer back to the Introduction section above and summarize your findings of the sample you selected.
Discuss: Discuss whether you were surprised by the findings. Why or why not?
You can use the following tutorial that is specifically about this assignment:
MAT-240 Module 4 Project Two Video
https://www(dot)youtube(dot)com/watch?v=BBKHXuukXE0
What to Submit
To complete this project, you must submit the following:
Project Two Template Word Document Use this template to structure your report, and submit the finished version as a Word document.
Supporting Materials
The following resources may help support your work on the project:
Data Set: MAT 240 House Listing Price by Region Spreadsheet
Use this data for input in your project report.
Document: National Summary Statistics and Graphs House Listing Price by Region PDF
Use this data for input in your project report.
Use these tutorials for support with the Excel functions you will use in the project:
Tutorial: Random Sampling in Excel PDF
Tutorial: Scatterplots in Excel PDF
Tutorial: Descriptive Statistics in Excel PDF
Tutorial: Creating Histograms in Excel PDF

Essay Sample Content Preview:
Report: Regional vs National Housing Price Comparison
[Your Name]
University
Introduction
Region: Mountain Region was selected for this project
Purpose: This report's primary purpose is to assess whether the Mountain region's mean housing prices and square footage significantly differ from the national market average. The report aims to answer the following research questions:
* Are housing prices in the Mountain region lower than the national market average?
* Is the square footage for homes in the Mountain region different from the mean square footage for homes in the national market?
* What is the range of values for the 95% confidence interval of square footage for homes in the Mountain region market?
This project will use the following approach: A simple random sample of 500 observations from the Mountain region will be picked, then inference for means (one and two-tailed t-test) will be conducted, and lastly, a 95% confidence interval of square footage for homes in this region will be constructed.
Two hypotheses were formulated as follows;
* The Mountain's average housing prices are significantly lower than the national market.
* The mean square footage for homes in the Mountain region significantly differs from the mean square footage for homes in the national market.
Sample: A simple random sample of 500 observations from the house listing data in the Mountain region was obtained using the rand() function in excel. The variables included in the sample are County, State, House listing price, Square footage, and Cost per square foot.
Questions and type of test: Two hypothesis questions were formulated for this project: The first question is: Are housing prices in the Mountain region lower than the national market average? The population parameter being analyzed is the mean national house listing price. This parameter describes the average house price in a population of houses listed in the United States. The null hypothesis formulated for this question is that the average housing price in the Mountain region is equal to the national market average. On the other hand, the alternative hypothesis is that the average housing price in the Mountain region is lower than the national market average. The inference test that will be used is the one-tailed t-test (left-tailed) since we wish to test whether the population parameter (national house listing price) is lower than a specific value (mean housing price in the Mountain region).
The second hypothesis question that will be addressed is: Is the square footage for homes in the Mountain region different from the mean square footage for homes in the national market? The population parameter being analyzed is the mean national Square Feet. The null hypothesis formulated for this question is that the mean square footage for homes in the Mountain region is not significantly different from the mean square footage for homes in the national market. On the other hand, the alternative hypothesis is that the mean square footage for homes in the Mountain region is significantly different from the mean square footage for homes in the national market. A two-tailed t-test will be used since we wish to compare the means of the mountain region and the nationa...
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