H1: mu > 30 represents which tailed test?
Right
True or False.... When sigma is unknown, we are given a sample standard deviation (s) instead.
True
What is the formula for calculating phat?
r/n
An alternative hypothesis is detonated as_____
H1
If P(value) > alpha then we.......
Fail to Reject Ho
What P(Value) matches with a right tailed test and the z value of 0.90?
0.1841
If we don't know sigma, we must find (blank) values instead of z values.
t
What is the formula for calculating the test statistic (z score) of a proportion problem?
z = phat - p/ sprt(pq/n)
In a null hypothesis, the statement is always mu ________ to some number.
=
When we complete this problems, do we actually prove anything? Explain your answer.
No, .....
What P(value) matches up with a two tailed test and z=1.98?
0.0239 ----> times 2 -----> 0.0478
Find your test statistic t when mu-12.5, s=10, n=21, and x bar=17.1.
2.108
State the null and alternate hypothsis's.
Let p=0.75. We think the actual proportion is simply different from p.Ho: p=0.75
H1: p /= 0.75
Ho: mu=60 and H1: mu <60
Find the test statistic z for the following info. Let mu=115, sigma=12, n=6 and x bar=105.
-2.04
To find the correct row to use in the chart, you need to calculate (blank) which is found by taking n-1
Degrees of freedom
Let alpha = 0.01 and p=0.12. Then, let phat = 0.0766. The sample size is 209. We want to test is if the population is less than 0.12. Find the z score, P(value), and then state whether we reject or not.
0.0268 ---> Fail to reject Ho
Let z=1.08. We are doing a right tailed test with alpha=0.05. Determine if we reject or fail to reject using the critical region method. Sketch a picture.
z=1.08 and znot = 1.645
So z falls outside the region ----> We fail to reject Ho
Determine if we will fail to reject or will reject Ho.
Let x bar =17.1, sigma=4.5, mu = 19, n=500 and the level of significance =0.05. We want to test if mu is less than 19.
0.0571 ---> Fail to reject Ho.
Find an estimate/interval for the P(value) given the following t value: 2.940?
0.0005 < P(Value) < 0.005