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Statistics
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Southern New Hampshire University
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Hypothesis Testing for Regional Real Estate Company 1
Hypothesis Testing for Regional Real Estate Company
[Your Name]
Southern New Hampshire University

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Hypothesis Testing for Regional Real Estate Company 2
Introduction
The Regional Real Estate Company sales properties for people. One of the salespeople of
the company in Pacific region have a problem with newly designed advertisement it states that
the average cost per square foot of his home sales is above the average cost per square foot in the
Pacific region but he is not sure of the statement. Therefore, the purpose of this analysis is to test
and justify if the sales person claim is true before using the newly designed advertisement.
Setup
The population parameter for this analysis is the average sales price per square foot (µ) in
the Pacific region. The claim in the newly designed advertisement is made on the sale price of
homes per square foot; therefore, the home sales price per foot in the region is the parameter of
interest for this study. The hypothesis are
H
0
: There is no significance different between the salesperson average sales price and µ
= $275 at a 5% significance level
H
1
: The average sales price of the salesperson is significantly different from the $275 at
5% significance level.
0
1
:$275
:$275
HX
HX
=
Significance level α = 0.05
The study will use t-test statistics because the aim of analysis is to test the difference
between the population mean and claimed mean by the salesperson. Since the sales person claim
that his sales price is higher than the population price the left-tailed test was used.

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Hypothesis Testing for Regional Real Estate Company Hypothesis Testing for Regional Real Estate Company [Your Name] Southern New Hampshire University 1 Hypothesis Testing for Regional Real Estate Company 2 Introduction The Regional Real Estate Company sales properties for people. One of the salespeople of the company in Pacific region have a problem with newly designed advertisement it states that the average cost per square foot of his home sales is above the average cost per square foot in the Pacific region but he is not sure of the statement. Therefore, the purpose of this analysis is to test and justify if the sales person claim is true before using the newly designed advertisement. Setup The population parameter for this analysis is the average sales price per square foot (µ) in the Pacific region. The claim in the newly designed advertisement is made on the sale price of homes per square foot; therefore, the home sales price per foot in the region is the parameter of interest for this study. The hypothesis are H0: There is no significance different between the salesperson average sales price and µ = $275 at a 5% significance level H1: The average sales price of the salesperson is significantly different from the $275 at 5% significance level. H 0 : $275 = X H1 : $275  X Significance level α = 0.05 The study will use t-test statistics because the aim of analysis is to test the difference between the population mean and claimed mean by the salesperson. Since ...
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