You're looking for the extreme values of 
subject to the constraint 
.
The target function has partial derivatives (set equal to 0)
so there is only one critical point at 
. But this point does not fall in the region . There are no extreme values in the region of interest, so we check the boundary.
Parameterize the boundary of by
with 
. Then 
can be considered a function of 
alone:
has critical points where 
:
but 
for all , so this case yields nothing important.
At these critical points, we have temperatures of
so the plate is hottest at (1, 0) with a temperature of 14 (degrees?) and coldest at (-1, 0) with a temp of -12.
Step-by-step explanation:
Given precision is a standard deviation of s=1.8, n=12, target precision is a standard deviation of σ=1.2
The test hypothesis is
H_o:σ <=1.2
Ha:σ > 1.2
The test statistic is
chi square = 
=
=24.75
Given a=0.01, the critical value is chi square(with a=0.01, d_f=n-1=11)= 3.05 (check chi square table)
Since 24.75 > 3.05, we reject H_o.
So, we can conclude that her standard deviation is greater than the target.
It will have the same value. The slope of the mid-segment of DE is just equal to the slope of the segment of AC. This is because of the mid-segment theorem stating that both slopes of a triangle have same value. So the answer is -0.4 for both segments.
Answer:
Natural numbers (integers greater than zero)
X = 3, 5, 4, 4, 3
Step-by-step explanation:
The least number of cars that can be observed in this experiment is 1, if the first car turns left. On the other hand, the experiment could go on forever if no car ever turns left, thus the highest number of cars approaches infinite.
The possible values of X are integers greater than zero, which are known as the Natural numbers.
If X = number of cars observed, simply count the number of letters in each outcome for the value of X:
Outcome = RRL, AARRL, AARL, RRAL, ARL
X = 3, 5, 4, 4, 3
