Answer:
Radians
<em>Hope that helps!</em>
Step-by-step explanation:
Answer:
As 
Step-by-step explanation:
Given:
From the graph, we can conclude that:
The function has vertical asymptotes at 
The function has horizontal asymptote at 
Vertical asymptotes are those values of 'x' for which the functions tends towards infinity. Horizontal asymptote is the value of the function as the 'x' value tends to infinity.
Now, as
means the right hand limit of the function at 
From the graph, the right hand limit is the right side of the asymptote of the function at
. The right side shows that the function is tending towards negative infinity.
Therefore, As 
Answer:
the dimension of the poster = 90 cm length and 60 cm width i.e 90 cm by 60 cm.
Step-by-step explanation:
From the given question.
Let p be the length of the of the printed material
Let q be the width of the of the printed material
Therefore pq = 2400 cm ²
q = 
To find the dimensions of the poster; we have:
the length of the poster to be p+30 and the width to be 
The area of the printed material can now be: 
=
Let differentiate with respect to p; we have

Also;

For the smallest area 


p² = 3600
p =√3600
p = 60
Since p = 60 ; replace p = 60 in the expression q =
to solve for q;
q =
q = 
q = 40
Thus; the printed material has the length of 60 cm and the width of 40cm
the length of the poster = p+30 = 60 +30 = 90 cm
the width of the poster =
=
= 40 + 20 = 60
Hence; the dimension of the poster = 90 cm length and 60 cm width i.e 90 cm by 60 cm.
Answer:
Option B - False
Step-by-step explanation:
Critical value is a point beyond which we normally reject the null hypothesis. Whereas, P-value is defined as the probability to the right of respective statistic which could either be Z, T or chi. Now, the benefit of using p-value is that it calculates a probability estimate which we will be able to test at any level of significance by comparing the probability directly with the significance level.
For example, let's assume that the Z-value for a particular experiment is 1.67, which will be greater than the critical value at 5% which will be 1.64. Thus, if we want to check for a different significance level of 1%, we will need to calculate a new critical value.
Whereas, if we calculate the p-value for say 1.67, it will give a value of about 0.047. This p-value can be used to reject the hypothesis at 5% significance level since 0.047 < 0.05. But with a significance level of 1%, the hypothesis can be accepted since 0.047 > 0.01.
Thus, it's clear critical values are different from P-values and they can't be used interchangeably.