Chat with us, powered by LiveChat You have been hired by your regional real estate company to determine if your regions housing prices and housing square footage are significantly different from those of the national - Writingforyou

You have been hired by your regional real estate company to determine if your regions housing prices and housing square footage are significantly different from those of the national

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:

  1. Are housing prices in your regional market lower than the national market average?
  2. Is the square footage for homes in your region different than the average square footage for homes in the national market?
  3. 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

  1. 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
  2. Purpose: What is the purpose of your analysis?
  3. Sample: Define your sample. Take a random sample of 500 house sales for your region.
    1. Describe what is included in your sample (i.e., states, region, years or months).
  4. Questions and type of test: For your selected sample, define two hypothesis questions (see the Scenario above) and the appropriate type of test for each. Address the following for each hypothesis:
    1. Describe the population parameter for the variable you are analyzing.
    2. Describe your hypothesis in your own words.
    3. Identify the hypothesis test you will use (1-Tail or 2-Tail).
  5. Level of confidence: Discuss how you will use estimation and confidence intervals to help you solve the problem.

1-Tail Test

  1. Hypothesis: Define your hypothesis.
    1. Define the population parameter.
    2. Write null (Ho) and alternative (Ha) hypotheses. Note: For means, define a hypothesis that is less than the population parameter.
    3. Specify your significance level.
  2. Data analysis: Summarize your sample data using appropriate graphical displays and summary statistics and confirm assumptions have not been violated to complete this hypothesis test.
    1. Provide at least one histogram of your sample data.
    2. In a table, provide summary statistics including sample size, mean, median, and standard deviation. Note: For quartiles 1 and 3, use the quartile function in Excel:
      =QUARTILE([data range], [quartile number])
    3. Summarize your sample data, describing the center, spread, and shape in comparison to the national information (under Supporting Materials, see the National Summary Statistics and Graphs House Listing Price by Region PDF). Note: For shape, think about the distribution: skewed or symmetric.
    4. Check the conditions.
      1. Determine if the normal condition has been met.
      2. Determine if there are any other conditions that you should check and whether they have been met. Note: Think about the central limit theorem and sampling methods.
  3. Hypothesis test calculations: Complete hypothesis test calculations.
    1. Calculate the hypothesis statistics.
      1. Determine the appropriate test statistic (t). Note: This calculation is (mean – target)/standard error. In this case, the mean is your regional mean, and the target is the national mean.
      2. Calculate the probability (p value). Note: This calculation is done with the T.DIST function in Excel:
        =T.DIST([test statistic], [degree of freedom], True) The degree of freedom is calculated by subtracting 1 from your sample size.
  4. Interpretation: Interpret your hypothesis test results using the p value method to reject or not reject the null hypothesis.
    1. Relate the p value and significance level.
    2. Make the correct decision (reject or fail to reject).
    3. Provide a conclusion in the context of your hypothesis.

2-Tail Test

  1. Hypotheses: Define your hypothesis.
    1. Define the population parameter.
    2. Write null and alternative hypotheses. Note: For means, define a hypothesis that is not equal to the population parameter.
    3. State your significance level.
  2. Data analysis: Summarize your sample data using appropriate graphical displays and summary statistics and confirm assumptions have not been violated to complete this hypothesis test.
    1. Provide at least one histogram of your sample data.
    2. In a table, provide summary statistics including sample size, mean, median, and standard deviation. Note: For quartiles 1 and 3, use the quartile function in Excel:
      =QUARTILE([data range], [quartile number])
    3. Summarize your sample data, describing the center, spread, and shape in comparison to the national information. Note: For shape, think about the distribution: skewed or symmetric.
    4. Check the assumptions.
      1. Determine if the normal condition has been met.
      2. Determine if there are any other conditions that should be checked on and whether they have been met. Note: Think about the central limit theorem and sampling methods.
  3. Hypothesis test calculations: Complete hypothesis test calculations.
    1. Calculate the hypothesis statistics.
      1. Determine the appropriate test statistic (t). Note: This calculation is (mean – target)/standard error. In this case, the mean is your regional mean, and the target is the national mean.]
      2. Determine the probability (p value). Note: This calculation is done with the TDIST.2T function in Excel:
        =T.DIST.2T([test statistic], [degree of freedom]) The degree of freedom is calculated by subtracting 1 from your sample size.
  4. Interpretation: Interpret your hypothesis test results using the p value method to reject or not reject the null hypothesis.
    1. Compare the p value and significance level.
    2. Make the correct decision (reject or fail to reject).
    3. Provide a conclusion in the context of your hypothesis.
  5. Comparison of the test results: Revisit Question 3 from the Scenario section: For your region, what is the range of values for the 95% confidence interval of square footage for homes?
    1. Calculate and report the 95% confidence interval. Show or describe your method of calculation.

Final Conclusions

  1. Summarize your findings: In one paragraph, summarize your findings in clear and concise plain language.
  2. 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:

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. (attachment: template)

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. (attachment House listing)

Document: National Summary Statistics and Graphs House Listing Price by Region PDF
Use this data for input in your project report. 

link: https://learn.snhu.edu/content/enforced/1261476-MAT-240-J4761-OL-TRAD-UG.23EW4/course_documents/National%20Summary%20Statistics%20and%20Graphs%20House%20Listing%20Price%20by%20Region.pdf?_&d2lSessionVal=VSwenxR7YPygxkB3gqtRHkFmP&ou=1261476

Regional vs. National Housing Price Comparison Report 2

[ 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

[Your Name]

Regional vs. National Housing Price Comparison Report 1

Southern New Hampshire University

Introduction

Region: [Clearly specify the region you picked from the list of regions mentioned in the Directions (West South Central, West North Central, East South Central, East North Central, Mid Atlantic).]

Purpose: [Define the purpose of the report.]

Sample: [Define your sample. Take a random sample of 500 house sales 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 (see the Scenario in the learning management system) and the appropriate type of test hypothesis for each.]

[First hypothesis: Describe the population parameter for the variable you are analyzing.]

[First hypothesis: Describe your hypothesis in your own words.]

[First hypothesis: Identify the hypothesis test you will use (1-Tail or 2-Tail).]

[Second hypothesis: Describe the population parameter for the variable you are analyzing.]

[Second hypothesis: Describe your hypothesis in your own words.]

[Second hypothesis: Identify the hypothesis test you will use (1-Tail or 2-Tail).]

Level of confidence: [Discuss how you will use estimation and confidence intervals to help you solve the problem.]

1-Tail Test

Hypothesis: [Define the population parameter.]

Hypothesis: [Write null (Ho) and alternative (Ha) hypotheses. Note: For means, define a hypothesis that is less than the population parameter.]

Hypothesis: [Specify your significance level.]

Data analysis: [Provide at least one histogram of your sample data.]

Data analysis: [In a table, provide summary statistics including sample size, mean, median, and standard deviation.

Note: For quartiles 1 and 3, use the quartile function in Excel:]

=QUARTILE([data range], [quartile number])

Data analysis: [Summarize your sample data, describing the center, spread, and shape in comparison to the national information (Under “Supporting Materials,” see the National Summary Statistics and Graphs House Listing Price by Region PDF in the learning management system). Note: For shape, think about the distribution: skewed or symmetric.]

Data analysis: [Check the assumptions by determining if the normal condition has been met. Determine if there are any other conditions that you should check and whether they have been met. Note: Think about the central limit theorem and sampling methods.]

Hypothesis Test Calculations: [Determine the appropriate test statistic ( t). Note: This calculation is (mean – target)/standard error. In this case, the mean is your regional mean, and the target is the national mean.]

Hypothesis Test Calculations: [Calculate the probability ( p value). Note: This calculation is done with the T.DIST function in Excel:

=T.DIST([test statistic], [degree of freedom], True).

The degree of freedom is calculated by subtracting 1 from your sample size.]

Interpretation: [Compare the p value and significance level.]

Interpretation: [Make the correct decision (reject or fail to reject).]

Interpretation: [Provide a conclusion in the context of your hypothesis.]

2-Tail Test

Hypotheses: [Define the population parameter.]

Hypotheses: [Write null and alternative hypotheses. Note: For means, define a hypothesis that is not equal to the population parameter.]

Hypotheses: [State your significance level.]

Data Analysis: [Provide at least one histogram of your sample data.]

Data Analysis: [In a table, provide summary statistics including sample size, mean, and standard deviation. Note: For quartiles 1 and 3, use the quartile function in Excel: =QUARTILE([data range], [quartile number]) ]

Data Analysis: [Summarize your sample data, describing the center, spread, and shape in comparison to the national information. Note: For shape, think about the distribution: skewed or symmetric.]

Data Analysis: [Check the assumptions by determining if the normal condition has been met. Determine if there are any other conditions that you should check and whether they have been met. Note: Think about the central limit theorem and sampling methods.]

Hypothesis Test Calculations: [Determine the appropriate test statistic ( t). Note: This calculation is (mean – target)/standard error. In this case, the mean is your regional mean, and the target is the national mean.]

Hypothesis Test Calculations: [Calculate the probability ( p value). Note: This calculation is done with the TDIST.2T function in Excel: =T.DIST.2T([test statistic], [degree of freedom]). The degree of freedom is calculated by subtracting 1 from your sample size.]

Interpretation: [Relate the p value and significance level.]

Interpretation: [Make the correct decision (reject or fail to reject).]

Interpretation: [Provide a conclusion in context to your hypothesis.]

Comparison of the Test Results: [Calculate and report the 95% confidence interval. Show or describe the method of calculation.]

Final Conclusions

Summarize Your Findings: [In one paragraph, summarize your findings in clear and concise plain language.]

Discuss: [Discuss if you were surprised by the findings including why or why not.]

,

New England

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House Listing Price Data by Region Source: https://www.realtor.com/research/data/
Regional sample (n = 1001)
State County Region House listing price Cost per square foot Square footage
CT litchfield New England $329,050 $153 1,888
ME penobscot New England $169,500 $103 1,586
NH merrimack New England $299,950 $145 2,152
VT washington New England $289,950 $141 1,959
ME york New England $391,550 $230 1,719
VT washington New England $222,500 $135 1,670
NH strafford New England $311,471 $166 1,885
MA suffolk New England $699,050 $647 1,259
MA norfolk New England $642,500 $309 2,210
NH hillsborough New England $339,950 $164 2,090
RI washington New England $499,050 $259 1,871
NH belknap New England $289,950 $156 1,869
VT rutland New England $228,800 $117 1,993
RI newport New England $579,050 $292 2,128
MA franklin New England $230,050 $133 1,800
ME penobscot New England $157,050 $94 1,600
VT washington New England $300,050 $154 1,896
MA berkshire New England $379,950 $185 2,032
ME kennebec New England $187,050 $104 1,695
NH cheshire New England $266,550 $132 1,981
VT franklin New England $219,950 $120 1,750
CT new london New England $290,000 $153 1,848
NH merrimack New England $314,950 $146 2,174
NH merrimack New England $299,950 $140 2,176
NH hillsborough New England $358,950 $173 2,036
CT windham New England $204,000 $123 1,615
VT washington New England $295,050 $147 1,888
CT new london New England $268,500 $159 1,648
CT new haven New England $279,950 $158 1,724
MA plymouth New England $491,550 $244 2,028
MA franklin New England $223,800 $135 1,780
NH cheshire New England $260,500 $131 1,838
CT new haven New England $279,050 $153 1,790
ME penobscot New England $159,750 $100 1,588
NH grafton New England $259,300 $150 1,840
VT washington New England $299,050 $147 1,850
ME york New England $339,050 $205 1,772
CT new haven New England $272,421 $150 1,763
MA suffolk New England $764,050 $669 1,341
NH grafton New England $253,850 $143 1,741
RI newport New England $598,050 $292 2,170
MA middlesex New England $655,000 $276 2,400
MA franklin New England $299,050 $150 1,960
CT new london New England $274,950 $121 1,212
RI providence New England $279,050 $185 1,504
MA barnstable New England $599,950 $318 1,920
CT litchfield New England $398,050 $172 2,268
NH belknap New England $295,000 $162 1,838
NH belknap New England $269,950 $153 1,797
MA suffolk New England $799,050 $708 1,311
RI kent New England $275,050 $177 1,524
CT new haven New England $258,500 $146 1,410
VT windsor New England $349,050 $158 2,120
CT litchfield New England $329,950 $150 1,776
NH cheshire New England $234,550 $123 1,845
NH cheshire New England $258,864 $126 1,968
NH hillsborough New England $341,444 $160 2,126
RI washington New England $489,950 $253 1,812
CT middlesex New England $342,450 $170 1,874
CT new london New England $294,050 $154 1,880
NH strafford New England $284,950 $155 1,819
MA suffolk New England $774,500 $670 1,359
MA bristol New England $385,050 $210 1,873
MA bristol New England $375,050 $206 1,880
RI kent New England $319,950 $204 1,537
MA suffolk New England $722,500 $645 1,275
MA hampden New England $239,950 $145 1,668
ME kennebec New England $182,050 $108 1,678
MA suffolk New England $882,550 $760 1,385
VT chittenden New England $397,500 $180 2,162
CT hartford New England $263,707 $142 1,850
VT washington New England $279,050 $152 1,752
NH strafford New England $297,550 $149 1,852
CT hartford New England $247,750 $135 1,452
MA bristol New England $399,500 $215 1,847
CT new london New England $317,050 $164 1,884
MA norfolk New England $624,950 $284 2,303
RI bristol New England $499,950 $250 2,234
NH rockingham New England $410,050 $190 2,170