×

### Let's log you in.

or

Don't have a StudySoup account? Create one here!

×

or

## Week 4 Non-parametric Hypothesis Testing Team Paper (Real Estate)

by: smartwriter Notetaker

17

0

7

# Week 4 Non-parametric Hypothesis Testing Team Paper (Real Estate)

Marketplace > Week 4 Non parametric Hypothesis Testing Team Paper Real Estate
smartwriter Notetaker
CSU - Dominguez hills
GPA 3.0

Get a free preview of these Notes, just enter your email below.

×
Unlock Preview

Week 4 Non-parametric Hypothesis Testing Team Paper (Real Estate)
COURSE
PROF.
No professor available
TYPE
Study Guide
PAGES
7
WORDS
KARMA
50 ?

## Popular in Department

This 7 page Study Guide was uploaded by smartwriter Notetaker on Monday November 16, 2015. The Study Guide belongs to a course at a university taught by a professor in Fall. Since its upload, it has received 17 views.

×

## Reviews for Week 4 Non-parametric Hypothesis Testing Team Paper (Real Estate)

×

×

### What is Karma?

#### You can buy or earn more Karma at anytime and redeem it for class notes, study guides, flashcards, and more!

Date Created: 11/16/15
REAL ESTATE  1 Nonparametric Hypothesis Testing Learning Team B RES342 Research and Evaluation II Date Teacher REAL ESTATE  2 Introduction When conducting research a researcher must evaluate the various characteristics  of the data.  Many stages are used from the introduction of the research to the final  decision made in the conclusion.  Investing in a home for most people is the largest  investment he or she will make in a lifetime.  In the research conducted by Team B the  researchers have analyzed the relationship between the number of bedrooms in a house  and the cost per square foot of the house.  For a better understanding of how homes with  four or more bedrooms demand a higher market price the team will use a nonparametric  test.  Nonparametric tests are beneficial because they do not require the assumption  normality or assumption of homogeneity of variance.  Parametric tests are preferred  because for the same number of observations, they are more likely to lead to the rejection of a false null hypothesis (University of New England, 2000). In week three, Team B used a two sample hypothesis test to understand how the  number of bedrooms may impact the cost per square foot of the houses in the sample.   The result of the test was that the null hypothesis that houses with four bedrooms do not  have a higher mean selling price per square foot than houses with less than four  bedrooms.  This week, Team B uses a nonparametric hypothesis test to test the same data  to analyze the results of using a non­parametric test to evaluate the same research  question.  The problem statement was evaluated through a five­step hypothesis test using the Mann­Whitney nonparametric hypothesis test.  A two­tailed test will determine if the  REAL ESTATE  3 median price per square foot for houses with more than four bedrooms is different than  the median price per square foot for houses with less than four bedrooms. Step 1:  Hypothesis Hypothesis Null: The null hypothesis is that houses with four or more bedrooms  have the same price per square foot as houses with less than four bedrooms.   Hypothesis Alternate: The alternate hypothesis is that there is a significant  difference in the median prices of houses with four or more bedrooms than for houses  with less than four bedrooms.    Null Hypothesis H₀: M₁ = M₂ Alternate Hypothesis H₁: M₁ ≠ M₂ Step 2: Level of Significance Team B will test this hypothesis at the 0.05 significance level.  Step 3: Select the Test Statistic The large sample size (n  110, n  >20) we can use a z test.  The test statistic z is 1.645. Step 4 Formulate the decision rule Reject H 0  computed z is greater than 1.645 or if z is less than ­1.645.  Do not reject H 0 if computed value of z is less than 1.645 or is greater than ­1.645.  Alternatively, reject the null hypotheses if p­value is less than 0.05. REAL ESTATE  4 Z 0 051.645 Step 5 Compute value and make the decision Wilcoxon ­ Mann/Whitney Test n  sum of ranks  55 2998  Houses with 4 + BR 50 2567  Houses with <4 BR 105 5565  total 2915.00  expected value 155.86  standard deviation 0.53  z, corrected for ties .5966  p­value (two­tailed) Do not reject the null hypothesis H 0  the calculated z 0.53< 1.645 and p = .5966 is greater than .05. Conclusion           The research provided by Team B using the nonparametric Mann­Whitney test has  shown that the null hypothesis, which states that the median price per square foot for  houses with four bedrooms is not different than the median price per square foot for  houses with less than four bedrooms, cannot be rejected.   The nonparametric test results  REAL ESTATE  5 collaborates the parametric test results that were obtained using the hypothesis test for  independent groups performed during week three. The results of the analysis indicates that more research will be required to develop an  understanding of the key variable or variables that have the highest correlation with the  selling price of existing homes.  One proposed approach would be to conduct a more  exhaustive analysis including the incorporation of additional housing amenities such as  bathrooms, swimming pools, attached garages, and lot size and use ANOVA to evaluate  the effect of each variable on price – measuring both the effect of the variables both  within the groups and between the groups.   Appendix A – Charts REAL ESTATE  6 References University of New England. (2000). Nonparametric Tests. Retrieved from  http://www.une.edu.au/WebStat/unit_materials/c6_common_statistical_tests/nonp arametric_test.html     Doane, D. P. & Seward, L. E. (2007).  Applied statistics in business and economics.  Boston, MA: McGraw­Hill Irwin.  Retrieved March 12, 2011 from University of  Phoenix, Resource, RES­342—Business Research Methods II:  https://ecampus.phoenix.edu/classroom/ic/classroom.aspx REAL ESTATE  7

×

×

### BOOM! Enjoy Your Free Notes!

×

Looks like you've already subscribed to StudySoup, you won't need to purchase another subscription to get this material. To access this material simply click 'View Full Document'

## Why people love StudySoup

Bentley McCaw University of Florida

#### "I was shooting for a perfect 4.0 GPA this semester. Having StudySoup as a study aid was critical to helping me achieve my goal...and I nailed it!"

Anthony Lee UC Santa Barbara

#### "I bought an awesome study guide, which helped me get an A in my Math 34B class this quarter!"

Steve Martinelli UC Los Angeles

#### "There's no way I would have passed my Organic Chemistry class this semester without the notes and study guides I got from StudySoup."

Parker Thompson 500 Startups

#### "It's a great way for students to improve their educational experience and it seemed like a product that everybody wants, so all the people participating are winning."

Become an Elite Notetaker and start selling your notes online!
×

### Refund Policy

#### STUDYSOUP CANCELLATION POLICY

All subscriptions to StudySoup are paid in full at the time of subscribing. To change your credit card information or to cancel your subscription, go to "Edit Settings". All credit card information will be available there. If you should decide to cancel your subscription, it will continue to be valid until the next payment period, as all payments for the current period were made in advance. For special circumstances, please email support@studysoup.com

#### STUDYSOUP REFUND POLICY

StudySoup has more than 1 million course-specific study resources to help students study smarter. If you’re having trouble finding what you’re looking for, our customer support team can help you find what you need! Feel free to contact them here: support@studysoup.com

Recurring Subscriptions: If you have canceled your recurring subscription on the day of renewal and have not downloaded any documents, you may request a refund by submitting an email to support@studysoup.com