Discussion:
Q: Implement raw data tables and computations, using both graphical and tabular methods of displaying data and results Two or More Sample Hypothesis Testing Paper
Hypothesis
The US economy is in crisis brought on by the financial markets, the deep slump of the housing, high unemployment, and the slowdown of consumer spending. This has caused problems for buyers and sellers in the real estate industry. Even in this downturn, there are still people looking for homes and this is a buyers' market. Because of the slow US economy, there is an abundance of homes available for purchase brought on by high unemployment, and foreclosures.
Because of the abundance of homes on the market, buyers are able to purchase more amenities, such as homes with more than one bedroom, bathrooms, a pool, and with more square footage. Even in this stalled economy, those additional amenities all have an impact on the selling price of a home. The objective of this research using the Real Estate Data sets will determine if there is a difference in the mean price per square foot between three and four bedroom homes. The sample will consist of 26 three bedroom and 26 four bedroom homes. This research will determine if the hypotheses should be accepted or rejected. Given the data mentioned above:
The verbal hypothesis the research will determine if there is a difference in the mean price per square foot between three and four bedroom homes.. The mean for the three bedroom homes is 2,165 with a standard deviation of 210. The mean for the four bedroom homes is 2,308 with a standard deviation of 251. The hypothesis will determine if the price square foot is equal or not equal between the two samples.
The numerical hypothesis is:
H0: µ1 = µ2
H1: µ1 ≠ µ2
Five-Step Hypothesis Test
As stated, the information given gives us
3 Bedrooms 4 Bedrooms
x1 = 2165 x2 = 2308
s1 = 210 s2 = 251
n1 = 26 n2 = 26
The hypothesis tests are:
H0: µ1 = µ2
H1: µ1 ≠ µ2
Therefore, the following represents data used and steps taken to verify the hypothesis using the five step process.
Descriptive statistics 4 bedroom
Size
count 26
mean 2,307.69
sample variance 63,138.46
sample standard deviation 251.27
minimum 1900
maximum 2900
range 1000
population variance 60,710.06
population standard deviation 246.39
standard error of the mean 49.28
confidence interval 95.% lower 2,206.20
confidence interval 95.% upper 2,409.18
half-width 101.49
empirical rule
mean - 1s 2,056.42
mean + 1s 2,558.97
percent in interval (68.26%) 73.1%
mean - 2s 1,805.14
mean + 2s 2,810.24
percent in interval (95.44%) 92.3%
mean - 3s 1,553.87
mean + 3s 3,061.51
percent in interval (99.73%) 100.0%
Descriptive statistics 3 bedroom
Size
count 26
mean 2,165.38
sample variance 43,953.85
sample standard deviation 209.65
minimum 1600
maximum 2500
range 900
population variance 42,263.31
population standard deviation 205.58
standard error of the mean 41.12
confidence interval 95.% lower 2,080.70
confidence interval 95.% upper 2,250.06
half-width 84.68
empirical rule
mean - 1s 1,955.73
mean + 1s 2,375.04
percent in interval (68.26%) 65.4%
mean - 2s 1,746.08
mean + 2s 2,584.69
percent in interval (95.44%) 96.2%
mean - 3s 1,536.43
mean + 3s 2,794.34
percent in interval (99.73%) 100.0%