Unformatted text preview: .
5 (c) What is the p-value associated with the test statistic used in the part (a)
test? Interpret this value. The p-value is the probability of obtaining a test statistic more extreme than
the realized value, assuming the null hypothesis is true. The lower the p -value,
the greater is the evidence for rejection of the null hypothesis. In this case it is
very unlikely to find a sample mean as extreme as $265,000 given a population
mean of $250,000.
(d) Define the type I and II errors in the context of the part (a) test. Type I Error: Concluding that housing price is more than $250,000, while it is
Type II Error: Not being able to reject the claim that housing price is $250,000,
while it is really more. 3. What effect does increasing the sample size have on the outcome of a
hypothesis test? Explain your answer using the example of a one -tail test
concerning the mean of a normally distributed population with known
variance. (It is expected that students will find this question difficult)
Suppose an upper tail test Under
The point ( ) on N(0,1) corresponds to the point
distribution of ̅
̅ √ on...
View Full Document
- Statistics, Statistical hypothesis testing, Type I and type II errors, α, upper tail test