MAT 240 Project Two Template (1)

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Regional vs. National Housing Price Comparison Report 1 [ Note: To complete this template, replace the bracketed text with your own content. Remove this note before you submit your outline.] Report: Regional vs. National Housing Price Comparison Asia Jones Motley Southern New Hampshire University

Regional vs. National Housing Price Comparison Report 2 Introduction Region : Real estate companies invest in constructing houses which they later sell or rent out. This study focuses on the listing prices of homes in various regions of the US. Specifically, the study will concentrate on the East North Central region, and then compare its data with the national market. Purpose : For my current study, I will be using statistical inferencing methods to analyze the means of house sales in the East North Central region. I will apply sampling and various statistical techniques to examine the hypothesis. There will be two variables in my sample. In order to formulate policies, we need to analyze the data. As I have been hired by the D.M Estate company, my objective is to determine if the prices of houses and square feet in East North Central region are statistically different from the national market. A full report will be compiled for the regional sales director once I complete my analysis. Sample : I will analyze the means of house sales in the East North Central region using statistical inferencing methods. For this, I will use a sample of 500 observations collected randomly using the "=RAND()" function in Excel. The data sets include county names, regions, states, listing price, and square feet in the U.S. I will use various statistical techniques and sampling to examine the hypothesis. My objective is to determine if the prices of houses and square footage in the East North Central region differ significantly from the national market. I have been hired by the D.M Estate company for this purpose. Once I complete my analysis, I will prepare a comprehensive report for the regional sales director based on the data analysis, which can help with policy formulation. Questions and type of test: What is the average square footage of homes in the East North Central region compared to the national average?

Regional vs. National Housing Price Comparison Report 3 Which area of the East North Central region has the highest 95% confidence interval for square footage? I will therefore utilize the quantitative analysis method to address the above-mentioned questions through the use of summary statistics and t-test analyses. One t Test Ho: µ = µo (288,407) H1: µ < µo (288,407) To assess the significance of the study, I will use an alpha value of 5%, and in concluding, I will compare the p-value with the significance level using the p-value approach.

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Regional vs. National Housing Price Comparison Report 4 Ho: µ = µo (288,407) H1: µ < µo (288,407) A significance level of 5% will be used to assess the significance of the study, and I will use the p-value approach to compare the p-value with the significance level. One t Test Ho: µ = µo (288,407) H1: µ < µo (288,407) To assess the significance of the study, I will use an alpha value of 5%, and in concluding, I will compare the p-value with the significance level using the p-value approach.

Regional vs. National Housing Price Comparison Report 5

Regional vs. National Housing Price Comparison Report 6 The fourth Regional vs. National Housing Price Comparison Report presents the results in Table 1. The mean square feet was calculated to be 1810.87 with a standard deviation of 357.82. The mean listing price was 195630.50 with a standard deviation of 80291.33. This indicates that both variables were widely dispersed from their mean averages. The information was analyzed and presented using histograms, which are shown in the report. The histogram indicates a right-skewed distribution of listing prices with no outliers present. The data was uniform, and the skewness value was 0.79, indicating normal distribution. 1-Tail Test I will use a quantitative method, specifically the one-sample t-test, to answer the first director's question. According to the data provided in Table 2, the p-values were stated as p = 1.00 > 0.05. Consequently, at a significance level of 5%, the null hypothesis (Ho) was accepted, indicating that East North Central house listing prices are lower than national house listing prices. 2-Tail Test Hypothesis: [Two-tailed t-Test Ho: µ = H1: µ ≠

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Regional vs. National Housing Price Comparison Report 7 Data analysis: The data presented in Table 1 indicates that the mean square footage was 1810.87 with a standard deviation of 357.82, signifying that the values are widely dispersed from the average mean. The histogram depicted in Figure 2 shows that the square footage is skewed to the right,

Regional vs. National Housing Price Comparison Report 8 without any outliers present. The calculated skewness value was 2.04, suggesting that the data is normally distributed. Based on the findings presented in Table 3, it was observed that the p- value is reported as p=1.00, which is far higher than the level of 0.05. Therefore, the null hypothesis (Ho) was granted, which led to the solution that the square footage in the East North Central region was the same as the national market at the 5% level of significance. . 95% Confident

Regional vs. National Housing Price Comparison Report 9 After analyzing the data in Table 4, I can say with 95% confidence that the square footage of the East North Central region falls between the range of values (1780.898, 1840.838), which indicates the actual value of the population parameter. Final Conclusions Summarize Your Findings: [The aim of the study was to determine if the prices of houses and square footage in the East North Central region differ from the national market. A normal distribution was found for all variables, with the mean listing price being 195630.50 (SD=80291.33), and the mean square footage being 1810.87 (SD=357.82). It concluded that the house listing prices in the East North Central region were lower than the national market. However, the square footage in the East North Central region was equal to that of the national market. Furthermore, the 95% confidence interval for the square footage was [1780.898, 1840.838]. Based on Table 4, I can confidently say that the square footage of the East North Central region falls between the range of values (1780.898, 1840.838), indicating the actual value of the population parameter. Discuss : It was my expectation that the mean square footage would be within the range, so I was confident in my results. Hence, I strongly recommend investing in the East North Central region as it offers comparatively lower prices.

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