5. Calculations: 95% Confidence Interval
State: I am constructing a 95%
confidence interval that will estimate the
true difference in rent prices.
Plan: I will solve the margin of error and
use it in the formula
Solve:
Part I: Conditions are met (SRS,
Independent, sigma unknown)
Part II:
x1 4343.675
s1 1089.983
n1 40
df1 40-1 = 39
x2 2372.5
s2 1459.3226
n2 40
df2 40-1 = 39
Conclusion: I am 95% confident
that the true mean difference of
rent prices of San Francisco and
Chicago is between 1397 and
2545.
6. Calculations: Hypothesis Test 1-sample
State: I am testing the claim that on
average, rent in SF is more than
$2000
Plan I will use a hypothesis test to test
the claim.
Let μ= average rent price
H0 = μ=2000
HA = μ>2000
Solve:
Pt.I - Conditions are met (SRS, Independent,
sigma unknown)
Pt. II -Test Statistic
T-stat = 13.599021
Pt. III - P-value
Conclude:
Since p= is 0.0001 < α = .05, we
reject the null hypothesis. There is
enough evidence to suggest rent is
on average higher than $2000 in
SF.
7. Calculations: Hypothesis Test 2-sample
State: I am testing the claim that on
average, rent in SF is more than rent in
Chicago
Plan: I will use hypothesis test to test
the claim
Let μ1= average rent in SF
Let μ2= average rent in Chi.
Solve:
Pt.I - Conditions are met (SRS,
Independent, sigma unknown)
Pt. II -Test Statistic
x1 4343.675
s1 1089.983
n1 40
df1 40-1 = 39
x2 2372.5
s2 1459.3226
n2 40
df2 40-1 = 39
Pt. III- p-value = 0.0001
Conclusion: Since p= is 0.0001 < α
= .05, we reject the null hypothesis.
There is enough evidence to suggest
rent is higher in SF than in Chicago.
8. Data Analysis and Conclusion
-Data may be biased because of the algorithms favoring newer postings versus old ones
-Further bias because postings showed multiple rooms by building; skipped over some to diversify listings
-Rent is higher in San francisco than Chicago
-More than double the rent in San Francisco than Chicago