Here is a condensed solution
By using the reciprocal identity the value
will be ![\dfrac{5}{27}{](https://tex.z-dn.net/?f=%5Cdfrac%7B5%7D%7B27%7D%7B)
<h3>What is Reciprocal and Quotient Identities?</h3>
In trigonometry, quotient identities refer to trig identities that are divided by each other.
So here we have
![Cosec\theta = \dfrac{27}{5}](https://tex.z-dn.net/?f=Cosec%5Ctheta%20%3D%20%5Cdfrac%7B27%7D%7B5%7D)
Now we have to find the reciprocal identity,
![Sin\theta=\dfrac{1}{Cosec\theta}](https://tex.z-dn.net/?f=Sin%5Ctheta%3D%5Cdfrac%7B1%7D%7BCosec%5Ctheta%7D)
![Sin\theta}=\dfrac{1}{\dfrac{27} { 5} }](https://tex.z-dn.net/?f=Sin%5Ctheta%7D%3D%5Cdfrac%7B1%7D%7B%5Cdfrac%7B27%7D%20%7B%205%7D%20%7D)
![Sin\theta=\dfrac{5}{27}](https://tex.z-dn.net/?f=Sin%5Ctheta%3D%5Cdfrac%7B5%7D%7B27%7D)
hence by using the reciprocal identity the value
will be ![\dfrac{5}{27}{](https://tex.z-dn.net/?f=%5Cdfrac%7B5%7D%7B27%7D%7B)
To know more about Reciprocating identity follow
brainly.com/question/15769816
#SPJ1
The slope is -1/2 or -0.5
Answer:
B. No, because while there is no linear correlation, there may be a relationship that is not linear.
Step-by-step explanation:
Relationships between variables are diverse and fitted model of a dataset for each of the models will usually differ. That is the lebl of association between variables for a linear model may differ and better than a quadratic model or an exponential may perform. For r = 0 ; this means no relationship exists between the variables, however , this is the information for the linear model, which clearly depicts that no assicitio exist for the linear fit. A model change could result in a differ and slightly or highly correlated R value.
Answer:
P(X1) = 1, P(X2)= 2/3, P(X3)= 2/3, P(X4)= 1/3, P(X5)= 2/3, P(X6)= 1/3, P(X7)= 1/3 and P(X8)= 0
Step-by-step explanation: