Numerade

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ANSWERED

Donna Densmore

Numerade educator

In this course, you learned core applications of statistical analysis to solve real-world personal or professional inquiry problems. You also learned different techniques to draw conclusions from data. These experiences allowed you to practice designing an approach to a statistical problem, considering assumptions and constraints, and developing interpretations and conclusions. Think about how you felt when you first started the course and how you feel now. Reflect on what you learned in this course and the applications of statistical concepts in your personal and professional life. In your initial discussion post, specifically address the following: 1.) What are some practical uses in your own life for the skills you gained in this class? 2.) How is data analysis changing in the world around you, including workplaces? 3.) How can statistics be persuasive and misleading? Please provide an example.

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Daniel Carr

Numerade educator

Housing prices in a small town are normally distributed with a mean of and a standard deviation of . Use the empirical rule to complete the following statement. Approximately of housing prices are between a low price ofand a high price of ..

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Rabia Sarwar

Numerade educator

Random Generated 30 Samples from East North Central: Region State County listing price $'s per square foot square feet East North Central in grant 219,500 $116 1,898 East North Central il vermilion 254,500 $156 1,632 East North Central in henry 235,000 $148 1,588 East North Central in wayne 203,800 $141 1,441 East North Central il coles 220,800 $117 1,893 East North Central il macoupin 197,600 $111 1,783 East North Central in vigo 165,800 $122 1,362 East North Central oh jefferson 246,500 $136 1,814 East North Central il jackson 154,300 $105 1,463 East North Central oh marion 149,700 $116 1,296 East North Central mi bay 145,100 $117 1,239 East North Central il whiteside 283,700 $136 2,087 East North Central oh trumbull 243,000 $133 1,827 East North Central in madison 229,100 $187 1,224 East North Central il knox 205,100 $118 1,740 East North Central stephenson 235,600 $140 1,682 East North Central il macon 212,900 $128 1,659 East North Central in delaware 221,600 $134 1,651 East North Central il henry 257,700 $123 2,087 East North Central oh seneca 211,900 $168 1,263 East North Central oh darke 160,800 $114 1,416 East North Central oh scioto 204,200 $131 1,562 East North Central oh belmont 172,500 $101 1,710 East North Central oh sandusky 253,900 $146 1,738 East North Central il rock island 166,300 $127 1,305 East North Central oh clark 240,500 $137 1,752 East North Central oh columbiana 241,400 $164 1,469 East North Central in howard 304,300 $152 1,996 East North Central oh richland 248,900 $132 1,880 East North Central = peoria 187,900 $131 1,434 Note: In the report you prepare for the sales team, the response variable (y) should be the listing price and the predictor variable (x) should be the square feet. 1.) Generate a Representative Sample of the Data - Select a region and generate a simple random sample of 30 from the data. - Report the mean, median, and standard deviation of the listing price and the square foot variables. 2.)Analyze Your Sample - Discuss how the regional sample created is or is not reflective of the national market. - Compare and contrast your sample with the population using the National Summary Statistics and Graphs Real Estate Data PDF document. - Explain how you have made sure that the sample is random. - Explain your methods to get a truly random sample.

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ANSWERED

Rabia Sarwar

Numerade educator

Region selected: Pacific 1.) Generate a Representative Sample of the Data - Select a region and generate a simple random sample of 30 from the data. - Report the mean, median, and standard deviation of the listing price and the square foot variables. 2.)Analyze Your Sample - Discuss how the regional sample created is or is not reflective of the national market. - Compare and contrast your sample with the population using the National Summary Statistics and Graphs Real Estate Data PDF document. - Explain how you have made sure that the sample is random. - Explain your methods to get a truly random sample. 3.) Generate Scatterplot - Create a scatterplot of the x and y variables noted above. Include a trend line and the regression equation. Label the axes. 4.) Observe patterns - Answer the following questions based on the scatterplot. - Define x and y. Which variable is useful for making predictions? - Is there an association between x and y? Describe the association you see in the scatter plot. - What do you see as the shape (linear or nonlinear)? - If you had a 1,800 square foot house, based on the regression equation in the graph, what price would you choose to list at? - Do you see any potential outliers in the scatterplot? - Why do you think the outliers appeared in the scatterplot you generated? - What do they represent?

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Rabia Sarwar

Numerade educator

Real Estate Data Spreadsheet Link: https://learn.snhu.edu/content/enforced/1754074-MAT-240-17462.202486-1/course_documents/MAT%20240%20Real%20Estate%20Data.xlsx?ou=1754074 Note: In the report you prepare for the sales team, the response variable (y) should be the listing price and the predictor variable (x) should be the square feet. 1.) Generate a Representative Sample of the Data - Select a region and generate a simple random sample of 30 from the data. - Report the mean, median, and standard deviation of the listing price and the square foot variables. 2.)Analyze Your Sample - Discuss how the regional sample created is or is not reflective of the national market. - Compare and contrast your sample with the population using the National Summary Statistics and Graphs Real Estate Data PDF document. - Explain how you have made sure that the sample is random. - Explain your methods to get a truly random sample. 3.) Generate Scatterplot - Create a scatterplot of the x and y variables noted above. Include a trend line and the regression equation. Label the axes. 4.) Observe patterns - Answer the following questions based on the scatterplot. - Define x and y. Which variable is useful for making predictions? - Is there an association between x and y? Describe the association you see in the scatter plot. - What do you see as the shape (linear or nonlinear)? - If you had a 1,800 square foot house, based on the regression equation in the graph, what price would you choose to list at? - Do you see any potential outliers in the scatterplot? - Why do you think the outliers appeared in the scatterplot you generated? - What do they represent?

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ANSWERED

Rabia Sarwar

Numerade educator

Real Estate Data Spreadsheet Link: https://learn.snhu.edu/content/enforced/1754074-MAT-240-17462.202486-1/course_documents/MAT%20240%20Real%20Estate%20Data.xlsx?ou=1754074 Note: In the report you prepare for the sales team, the response variable (y) should be the listing price and the predictor variable (x) should be the square feet. Complete this assignment: 1.) Generate a Representative Sample of the Data - Select a region and generate a simple random sample of 30 from the data. - Report the mean, median, and standard deviation of the listing price and the square foot variables. 2.)Analyze Your Sample - Discuss how the regional sample created is or is not reflective of the national market. - Compare and contrast your sample with the population using the National Summary Statistics and Graphs Real Estate Data PDF document. - Explain how you have made sure that the sample is random. - Explain your methods to get a truly random sample. 3.) Generate Scatterplot - Create a scatterplot of the x and y variables noted above. Include a trend line and the regression equation. Label the axes. 4.) Observe patterns - Answer the following questions based on the scatterplot. - Define x and y. Which variable is useful for making predictions? - Is there an association between x and y? Describe the association you see in the scatter plot. - What do you see as the shape (linear or nonlinear)? - If you had a 1,800 square foot house, based on the regression equation in the graph, what price would you choose to list at? - Do you see any potential outliers in the scatterplot? - Why do you think the outliers appeared in the scatterplot you generated? - What do they represent?

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Rabia Sarwar

Numerade educator

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ANSWERED

Rabia Sarwar

Numerade educator

Real Estate Data Spreadsheet Link: MAT 240 Real Estate Data.xlsx Note: In the report you prepare for the sales team, the response variable (y) should be the listing price and the predictor variable (x) should be the square feet. 1.) Generate a Representative Sample of the Data - Select a region and generate a simple random sample of 30 from the data. - Report the mean, median, and standard deviation of the listing price and the square foot variables. 2.)Analyze Your Sample - Discuss how the regional sample created is or is not reflective of the national market. - Compare and contrast your sample with the population using the National Summary Statistics and Graphs Real Estate Data PDF document. - Explain how you have made sure that the sample is random. - Explain your methods to get a truly random sample. 3.) Generate Scatterplot - Create a scatterplot of the x and y variables noted above. Include a trend line and the regression equation. Label the axes. 4.) Observe patterns - Answer the following questions based on the scatterplot. - Define x and y. Which variable is useful for making predictions? - Is there an association between x and y? Describe the association you see in the scatter plot. - What do you see as the shape (linear or nonlinear)? - If you had a 1,800 square foot house, based on the regression equation in the graph, what price would you choose to list at? - Do you see any potential outliers in the scatterplot? * Why do you think the outliers appeared in the scatterplot you generated? * What do they represent?

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ANSWERED

Rabia Sarwar

Numerade educator

Real Estate Data Spreadsheet Link: https://learn.snhu.edu/content/enforced/1754074-MAT-240-17462.202486-1/course_documents/MAT%20240%20Real%20Estate%20Data.xlsx?ou=1754074 You have been recently hired as a junior analyst by D.M. Pan Real Estate Company. The sales team has tasked you with preparing a report that examines the relationship between the selling price of properties and their size in square feet. You have been provided with a Real Estate Data Spreadsheet that includes properties sold nationwide in recent years. The team has asked you to select a region, complete an initial analysis, and provide the report to the team. Note: In the report you prepare for the sales team, the response variable (y) should be the listing price and the predictor variable (x) should be the square feet. 1.) Generate a Representative Sample of the Data - Select a region and generate a simple random sample of 30 from the data. - Report the mean, median, and standard deviation of the listing price and the square foot variables. 2.)Analyze Your Sample - Discuss how the regional sample created is or is not reflective of the national market. - Compare and contrast your sample with the population using the National Summary Statistics and Graphs Real Estate Data PDF document. - Explain how you have made sure that the sample is random. - Explain your methods to get a truly random sample. 3.) Generate Scatterplot - Create a scatterplot of the x and y variables noted above. Include a trend line and the regression equation. Label the axes. 4.) Observe patterns - Answer the following questions based on the scatterplot. - Define x and y. Which variable is useful for making predictions? - Is there an association between x and y? Describe the association you see in the scatter plot. - What do you see as the shape (linear or nonlinear)? - If you had a 1,800 square foot house, based on the regression equation in the graph, what price would you choose to list at? - Do you see any potential outliers in the scatterplot? * Why do you think the outliers appeared in the scatterplot you generated? * What do they represent?

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ANSWERED

Amna Khan

Numerade educator

Prompt You have been recently hired as a junior analyst by D.M. Pan Real Estate Company. The sales team has tasked you with preparing a report that examines the relationship between the selling price of properties and their size in square feet. You have been provided with a this Real Estate Data Spreadsheet link: (Real Estate Data Spreadsheet) that includes properties sold nationwide in recent years. The team has asked you to select a region, complete an initial analysis, and provide the report to the team. Note: In the report you prepare for the sales team, the response variable (y) should be the listing price and the predictor variable (x) should be the square feet. 1.) Generate a Representative Sample of the Data - Select a region and generate a simple random sample of 30 from the data. - Report the mean, median, and standard deviation of the listing price and the square foot variables. 2.)Analyze Your Sample - Discuss how the regional sample created is or is not reflective of the national market. - Compare and contrast your sample with the population using the National Summary Statistics and Graphs Real Estate Data PDF document. - Explain how you have made sure that the sample is random. - Explain your methods to get a truly random sample. 3.) Generate Scatterplot - Create a scatterplot of the x and y variables noted above. Include a trend line and the regression equation. Label the axes. 4.) Observe patterns - Answer the following questions based on the scatterplot. - Define x and y. Which variable is useful for making predictions? - Is there an association between x and y? Describe the association you see in the scatter plot. - What do you see as the shape (linear or nonlinear)? - If you had a 1,800 square foot house, based on the regression equation in the graph, what price would you choose to list at? - Do you see any potential outliers in the scatterplot? * Why do you think the outliers appeared in the scatterplot you generated? * What do they represent?

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Dylan Y.