# Check the question before bidding – statistics

Assignments to complete this week:

● Reading: Anderson et al. (14th ed.)

○ Chapter 15: Multiple regression

○ Chapter 18: Non-parametric methods

○ Chapter 9: The linear model (regression)

○ Chapter 7: Non-parametric models

● CLA 2 due by Sunday at 11:59 p.m.

Comprehensive Learning Assessment 2 – CLO 1, CLO 2, CLO 3, CLO 5, CLO 8, CLO 9, CLO 11, CLO 12

This assessment has two parts, for both parts, explain your work in detail and provide in-text citations.

1. Choose an affluent community and retrieve information about single family home listings from a real estate website. Retrieve needed information and perform the following tasks.

a. Please construct the descriptive statistics of the data before data analysis entailed in the following.

b. Develop a regression model in which living area is one independent variable, lot size is the other independent variable, and home price is the dependent variable. State the hypotheses on the coefficients, justify formulation of these hypotheses, and interpret the results. Use ɑ = .05. Include all phases of assessment of the model and do not forget to check multicollinearity.

c. Now include dummy variables in the model to reflect the effect of having a pool, and the effect of view. Repeat the steps mentioned in parts (a) and (b) for this case. Descriptive statistics in this case should be categorized by the values of the dummy variable. How different the model becomes when you include the effect of having a pool and view?

d. Provide a detailed description of how adding the pool as dummy variable impacts coefficient of determination.

e. Choose hypothetical living area and lot size to find the expected value – predicted listing price with and without a pool. Comment on your results.

1. Seasonal      data on the number of fatal lightings in the US is given in Table 16.

a. Formulate a two sided and a one-sided hypothesis on homogeneity of the median of the number of fatal lightings across the two seasons, and describe why Mann–Whitney–Wilcoxon (MWW) test is suitable for this purpose.

b. Provide descriptive statistics of the data as it pertains to this situation (graphical presentation is also required), test both hypotheses mentioned in part a, explain your work in detail, and interpret the result (to get critical values for testing the hypotheses please refer to users.stat.ufl.edu/~winner/tables/wilcoxonmannwhitney%5B1%5D.pdf).

Use ɑ = .05 in testing all hypotheses.

Table 16

Annual Data on   Frequencies of Lightings in Spring and Summer

Year

Spring

Summer

2017

12

2016

28

2015

17

11

2014

17

2013

15

2012

22

2011

19

2010

11

17

2009

15

18

2008

12

15

*Please refer to the Grading Criteria for Comprehensive Learning Assessments (CLAs) in the University Policies for specific guidelines and expectations.

Comprehensive Learning Assessment (CLA 2) Presentation