1. Are housing prices in your regional market higher than the national market average?
Population Parameter; Mean National market price of housing;
Null hypothesis: Mean regional market price of housing in my area less or equal to national
market average.
Alternative Hypothesis: Mean regional market price of housing in my area is higher than national
.market average.
This is a right tail test.
H0; U1 <= mu
H1: U1 >mu
U1 is the average housing price in my area and mu the average housing price in the national
market.
Inferential Test
Independent sample t-test
We have two means to compare, mean of the sample housing prices in my region and mean of
the national market price of housing. Thus we use independent sample t-test to asses whether
there is significant difference between the two means. The test statistic is the sample average
pricing of housing in my region.
If the p-value is less than the significance level, i will reject the null hypothesis else i will fail to
reject.
1. Is the square footage for homes in your region different than the average square footage
for homes in the national market?
Population parameter: Average square footage of homes in the national market.
Test Statistic: Average square footage of homes in my region.
Null Hypothesis: The average square footage of homes in my region is equal to the average
square footage for homes in the national market.
Alternative hypothesis: The average square footage of homes in my region is not equal to the
average square footage for homes in the national market.
This is a two tail test.
H0; U1 = mu
H1: U1!= mu
Inferential test.
There are two means to be compared, the average square footage of homes in my region and the
average square footage for homes in the national market. Independent sample t-test is appropriate
for determining whether there is statistically significant difference between the two means. The
test statistic is the average square footage of homes in my region.
If the p-value < significance level, i will reject the null hypothesis. Otherwise if the p-value >
significance level i will fail to reject the null hypothesis.
1. For your region, what is the range of values for the 95% confidence interval of square
footage for homes in your market"?
Population parameter: The average square footage for homes in the national market.
Null Hypothesis: The average square footage for homes in the national market lies outside in the
95% confidence interval of average square footage for homes in my region.
Alternative Hypothesis: The average square footage for homes in the national market lies in the
95% confidence interval of average square footage for homes in my region.
It is a two tail test.
This is interval estimation. The 95%conficence interval will give a range of plausible values that
the true average square footage for homes in the national market will lay.
The interval estimate is the range of possible values of average square footage for homes in my
region.
Step-by-step explanation
A null hypothesis is a statement of no difference between the sample and the population
parameter. If the p-value is less than the significance level then we reject the null hypothesis.
Otherwise, if p-value is larger than the significance level then there is insufficient evidence to
reject the null hypothesis.
