Answer:
its the 3rd one
Step-by-step explanation:
Recall that
and
for all
. So


For
, we expect both
and
(i.e. the sine and cosine of any angle that lies in the first quadrant must be positive). By definition of absolute value,
if
.
So we have

making H the answer.
C is always true, because the inequality reduces to x > y.
Answer:
Step-by-step explanation:
a)
Confidence interval in less than symbol expressed as

Where
is sample mean and
is margin of error.

b)
The given t interval is 
That is
and
Solve these two equation by adding together.
Solve this value of \bar{x} in equation
and solve for

Best point estimate of 
Best point estimate of margin of error = 0.193
c)
Since sample size = 100 which is sufficiently large (Greater than 30) , it is no need to confirm that
sample data appear to be form a population with normal distribution.