Answer: 2
Step-by-step explanation:
By the geometric mean theorem,

Answer:
See explanation
Step-by-step explanation:
(4)
Using the sine ratio in the right triangle
sinΘ =
=
, thus
Θ =
(
) ≈ 51.1°
(5)
Using the tangent ratio in the right triangle
tanΘ =
=
, thus
Θ =
(
) ≈ 38.7°
Answer:
The first statement is true.
Step-by-step explanation:
The function is f(x) = - (x + 6)(x + 2)
⇒ f(x) = - x² - 8x - 12
Now, condition for a function f(x) to be increasing at x = a is f'(a) > 0.
Now, f(x) = - x² - 8x - 12
⇒ f'(x) = -2x - 8 {Differentiating with respect to x}
Now, f'(a) = -2a - 8 {Here a can be any real value}
And, the condition for increasing function at x = a is
- 2a - 8 > 0
⇒ - 2a > 8
⇒ a < - 4
Therefore, the first statement is true i.e. the function is increasing for all real values of x where x < – 4. (Answer)
The magnitude and the direction of the resultant are approximately 57.871 and 198.676°.
<h3>How to determine the magnitude and the direction of a resultant</h3>
Vectors are elements with two given characteristics: Magnitude and direction. A resultant is derived from the sum of vectors, the magnitude is the norm of a vector and the direction is the orientation of a vector. The resultant and its characteristics are described below:
<h3>Resultant</h3>
(1)
<h3>Magnitude</h3>
(2)
<h3>Direction</h3>
(3)
Where
is resultant angle, measured in degrees.
If we know that
,
,
,
,
and
, then the resultant, its magnitude and its direction:
<h3>Resultant</h3>


<h3>Magnitude</h3>


<h3>Direction</h3>


The magnitude and the direction of the resultant are approximately 57.871 and 198.676°. 
To learn more on vectors, we kindly invite to check this verified question: brainly.com/question/13322477
Answer: Cluster Sampling
Step-by-step explanation:
In cluster sampling, researcher divides the population into groups ,which are called clusters. Then random sample of clusters are chosen ,and researcher conduct study to collect data about the population.
Here each bus is considered a cluster ,because busses are selected at random ,this sampling would be an example of cluster type of sampling.