Summary statistics column n mean std. dev. min q1 medi
1. Summary statistics:
Column n Mean Std. dev. Min Q1 Median Q3 Max
median listing price 978 288,407 163,986 75,309 186,742
256,936 337,342 1,653,763
median $'s per square
foot
978 142 92 21 95 121 157 1,084
median square feet 978 1,944 367 697 1,726 1,901 2,126 3,945
This graph shows the frequency for median listing price in
thousands.
The graph shows the frequency of median square feet.
20. England$399,050$1922,124CTtollandNew
England$272,000$1341,996CT…
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 higher 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. Purpose: What was the purpose of your analysis, and what is
21. your approach?
a. Define a random sample and two hypotheses (means) to
analyze.
2. Sample: Define your sample. Take a random sample of 100
observations for your region.
a. Describe what is included in your sample (i.e., states, region,
years or months).
3. 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:
a. Describe the population parameter for the variable you are
analyzing.
b. Describe your hypothesis in your own words.
c. Describe the inference test you will use.
i. Identify the test statistic.
4. Level of confidence: Discuss how you will use estimation and
conference intervals to help you solve the problem.
1-Tailed Test
1. Hypothesis: Define your hypothesis.
a. Define the population parameter.
b. Write null (Ho) and alternative (Ha) hypotheses.
c. Specify your significance level.
2. Data analysis: Analyze the data and confirm assumptions
have not been violated to complete this hypothesis test.
a. Summarize your sample data using appropriate graphical
displays and summary statistics.
i. Provide at least one histogram of your sample data.
ii. In a table, provide summary statistics including sample size,
mean, median, and standard deviation.
iii. Summarize your sample data, describing the center, spread,
and shape in comparison to the national information.
b. Check the conditions.
i. Determine if the normal condition has been met.
ii. Determine if there are any other conditions that you should
check and whether they have been met.
3. Hypothesis test calculations: Complete hypothesis test
22. calculations, providing the appropriate statistics and graphs.
a. Calculate the hypothesis statistics.
i. Determine the appropriate test statistic (t).
ii. Calculate the probability (p value).
4. Interpretation: Interpret your hypothesis test results using the
p value method to reject or not reject the null hypothesis.
a. Relate the p value and significance level.
b. Make the correct decision (reject or fail to reject).
c. Provide a conclusion in the context of your hypothesis.
2-Tailed Test
a. Hypotheses: Define your hypothesis.
1. Define the population parameter.
2. Write null and alternative hypotheses.
3. State your significance level.
b. Data analysis: Analyze the data and confirm assumptions
have not been violated to complete this hypothesis test.
b. Summarize your sample data using appropriate graphical
displays and summary statistics.
1. Provide at least one histogram of your sample data.
1. In a table, provide summary statistics including sample size,
mean, median, and standard deviation.
1. Summarize your sample data, describing the center, spread,
and shape in comparison to the national information.
b. Check the assumptions.
2. 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.
1. Hypothesis test calculations: Complete hypothesis test
calculations, providing the appropriate statistics and graphs.
c. Calculate the hypothesis statistics.
1. Determine the appropriate test statistic (t).
1. Determine the probability (p value).
1. Interpretation: Interpret your hypothesis test results using
the p value method to reject or not reject the null hypothesis.
d. Relate the p value and significance level.
d. Make the correct decision (reject or fail to reject).
23. d. Provide a conclusion in the context of your hypothesis.
1. Comparison of the test results: See Question 3 from the
Scenario section.
e. Calculate a 95% confidence interval. Show or describe your
method of calculation.
e. Interpret a 95% confidence interval.
Final Conclusions
1. Summarize your findings: Refer back to the Introduction
section above and summarize your findings of the sample you
selected.
2. Discuss: Discuss whether you were surprised by the findings.
Why or why not?
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
Purpose: [Include in this section a brief overview, the purpose
of the report, and your approach. Define your random sample
and two hypotheses (means) to analyze.]
Sample: [Take a random sample of observations from your
region and 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. For each hypothesis question, answer
questions 3a-c from the Project Two Guidelines and Rubric.
This includes questions about the population parameter, your
hypothesis, the inference method you will use, and how you will
use estimation and confidence intervals to help you solve the
24. problem.]
1-Tail Test
Hypothesis: [Define the population parameter. Write null and
alternative hypotheses. Note: For means, define a hypothesis
that is greater than the population parameter. Specify your
significance level.]
Data analysis: [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.]
Note: For quartiles 1 and 3, use the quartile function in Excel:
=QUARTILE([data range], [quartile number])
[Summarize your sample data, describing the center, spread, and
shape in context.]
[Note: For shape, think about the distribution: skewed or
symmetric.]
[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.]
[Calculate the probability (p value).]
[Note: This calculation is done with the T.DIST.RT function in
Excel: =T.DIST.RT([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.]
25. [Make the correct decision (reject or fail to reject).]
[Provide a conclusion in the context of your hypothesis.]
2-Tail Test
Hypotheses: [Define the population parameter. Write null and
alternative hypotheses.]
[Note: For means, define a hypothesis that is not equal to the
population parameter.]
[State your significance level.]
Data Analysis:
[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, and standard deviation.]
[Note: For quartiles 1 and 3, use the quartile function in Excel:
=QUARTILE([data range], [quartile number]) ]
[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.]
[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.]
[Calculate the probability (p value).]
[Note: This calculation is done with the TDIST.2T function in
Excel: =T.DIST.RT([test statistic], [degree of freedom]). The
degree of freedom is calculated by subtracting 1 from your
26. sample size.]
Interpretation:
[Relate the p value and significa nce level.]
[Make the correct decision (reject or fail to reject).]
[Provide a conclusion in context to your hypothesis.]
Comparison of the Test Results:
[Calculate the 95% confidence interval and show or describe the
method of calculation.]
[Interpret the confidence 95% confidence interval in context.]
Final Conclusions
[Summarize Your Findings: Refer back to Step 1 and summarize
your findings of the sample you selected.]
[Discuss: Discuss if you were surprised by the findings
including why or why not.]