Question Reflect on the relationships between square feet and sales price by addressing key considerations such as the comparison between your selected region and overall homes in the United States, as well as analyzing how the slope can help identify price changes, how the regression equation can help identify appropriate listing prices, and which graph would be best suited to informing square footage ranges Introduction Data This report is purposefully meant to reflect the relationship between the selling price of different properties and the size of the square feet The random sample of 30 from the South Atlantic regions have therefore been conducted in order to analyze the median listing price as the response variable and the predictor variable as the median square feet Representative Sample The data representative sample involves median listing selling price of $267, 367 and the mean being $ 284,575 and the standard deviation being $128,891 The median square cost was taken to be $122 5 and the mean being $137 together with the standard deviation of $65 Finally, the median square foot and the standard deviation to be 1963 33333 and 301 621633 respectively Region State County Median Listing $ Median $ per square foot Median Square foot South Atlantic GA Richmond 124,000 88 1553 South Atlantic WV Raleigh 143,884 78 1818 South Atlantic GA Clayton 146,217 69 1223 South Atlantic WV Wood 150,567 78 1683 South Atlantic NC Wilson 160,980 82 1830 South Atlantic NC Halifax 174,736 90 1827 South Atlantic SC Sumter 176,617 88 1993 South Atlantic SC Florence 187,452 94 1971 South Atlantic NC Onslow 214,996 113 1808 South Atlantic VA Norfolk City 228,177 139 1673 South Atlantic SC Lexington 235 722 103 2251 South Atlantic GA Camden 240,437 114 2000 South Atlantic WV Putnam 254,639 98 2296 South Atlantic VA Roanoke 255,141 121 2144 South Atlantic VA Richmond City 257,498 163 1636 South Atlantic WV Monongalia 277,236 132 2017 South Atlantic FL Volusia 283,880 158 1700 South Atlantic GA Walton 296,726 93 2066 Data Analysis To get the data analysis, the regional sample of South Atlantic region compared to the regional national market is compared thereafter noted that there is a higher value in the South Atlantic Region than there is compared to the market region Further sampling of 30 was randomly taken and 5 states from the region which tolls to 30, was placed in numerical order The placement in order enabled for the calculation of the median, mean, and standard deviation This also enabled for creation of clear ideas on how comparison of National Statistics and Graphs are made Further sampling of 30 was randomly taken and 5 different states from the region which tolls to 30 was placed in a numerical order The placement in order enabled for a calculation of the median, mean and standard deviation with ease The also enabled for the creation of clear ideas on how comparison of National Statistics and Graphs are made Scatterplot The Pattern To get the pattern, the X variable is taken to be median per square foot and variable Y to be median listing cost The X variable is most useful in making the prediction The amount of square feet is then determined by predicting the cost of living that would be obtained The association of the X and Y variable gives a scatterplot that maintains the same correlation with the one of the zero association According to the scatterplot, the outliers of the median listing are found to be $398,649 and $755,142 To conclude, it is noted that of one was to own a house of 1200 square feet, the base regression of the graph and the price to have the home listed would be approximately $140000 $135000 This is because the gra

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Question: Question - Reflect on the relationships between square feet and sales price by addressing key considerations such as the comparison between your selected region and

Question - Reflect on the relationships between square feet and sales price by addressing key considerations such as the comparison between your selected region and overall homes in the United States, as well as analyzing how the slope can help identify price changes, how the regression equation can help identify appropriate listing prices, and which graph would be best suited to informing square footage ranges.

Introduction

Data - This report is purposefully meant to reflect the relationship between the selling price of different properties and the size of the square feet.The random sample of 30 from the South Atlantic regions have therefore been conducted in order to analyze the median listing price as the response variable and the predictor variable as the median square feet.

Representative Sample

The data representative sample involves median listing selling price of $267, 367 and the mean being $ 284,575 and the standard deviation being $128,891. The median square cost was taken to be $122.5 and the mean being $137 together with the standard deviation of $65. Finally, the median square foot and the standard deviation to be 1963.33333 and 301.621633 respectively.

Region

State

County

Median Listing $

Median $ per square foot

Median Square foot

South Atlantic

Richmond

124,000

1553

South Atlantic

Raleigh

143,884

1818

South Atlantic

Clayton

146,217

1223

South Atlantic

Wood

150,567

1683

South Atlantic

Wilson

160,980

1830

South Atlantic

Halifax

174,736

1827

South Atlantic

Sumter

176,617

1993

South Atlantic

Florence

187,452

1971

South Atlantic

Onslow

214,996

113

1808

South Atlantic

Norfolk City

228,177

139

1673

South Atlantic

Lexington

235.722

103

2251

South Atlantic

Camden

240,437

114

2000

South Atlantic

Putnam

254,639

2296

South Atlantic

Roanoke

255,141

121

2144

South Atlantic

Richmond City

257,498

163

1636

South Atlantic

Monongalia

277,236

132

2017

South Atlantic

Volusia

283,880

158

1700

South Atlantic

Walton

296,726

2066

Data Analysis

To get the data analysis, the regional sample of South Atlantic region compared to the regional national market is compared thereafter noted that there is a higher value in the South Atlantic Region than there is compared to the market region.

Further sampling of 30 was randomly taken and 5 states from the region which tolls to 30, was placed in numerical order. The placement in order enabled for the calculation of the median, mean, and standard deviation.This also enabled for creation of clear ideas on how comparison of National Statistics and Graphs are made

Further sampling of 30 was randomly taken and 5 different states from the region which tolls to 30 was placed in a numerical order.The placement in order enabled for a calculation of the median, mean and standard deviation with ease.The also enabled for the creation of clear ideas on how comparison of National Statistics and Graphs are made.

Scatterplot

The Pattern

To get the pattern, the X variable is taken to be median per square foot and variable Y to be median listing cost.The X variable is most useful in making the prediction.The amount of square feet is then determined by predicting the cost of living that would be obtained.

The association of the X and Y variable gives a scatterplot that maintains the same correlation with the one of the zero association.According to the scatterplot, the outliers of the median listing are found to be $398,649 and $755,142.

To conclude, it is noted that of one was to own a house of 1200 square feet, the base regression of the graph and the price to have the home listed would be approximately $140000-$135000.This is because the gra

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