Answer:
The P-value is 0.0166.
Step-by-step explanation:
<u>The complete question is:</u> In a one-tail hypothesis test where you reject H0 only in the lower tail, what is the p-value if ZSTAT = -2.13.
We are given that the z-statistics value is -2.13 and we have to find the p-value.
Now, the p-value of the test statistics is given by the following condition;
P-value = P(Z < -2.13) = 1 - P(Z
2.13)
= 1 - 0.9834 = <u>0.0166</u>
Assuming that the level of significance is 0.10 or 10%.
The decision rule for rejecting the null hypothesis based on p-value is given by;
- If the P-value of the test statistics is less than the level of significance, then we have sufficient evidence to reject the null hypothesis.
- If the P-value of the test statistics is more than the level of significance, then we have insufficient evidence to reject the null hypothesis.
Here, the P-value is more than the level of significance as 0.0166 > 0.10, so we have insufficient evidence to reject the null hypothesis, so we fail to reject the null hypothesis.
M/3
OR
the quotient of a number, m, and 3
hope this helps :)
Answer:
y= -3y - 1/3x
Step-by-step explanation:
-2(x + 3y) = 18 Distribute the -2 to the x + 3y
-2x - 6y = 18
+2x +2x Add the 2x to both sides
-6y = 18 + 2x Divide both sides by -6
y= -3y - 1/3x
Round to the nearest whole number:
a) 14 ⇒ 13.5 ; 13.9 ; 14.1 ; 14.4
b) 28 ⇒ 27.5 ; 27.9 ; 28.1 ; 28.4
c) 32 ⇒ 31.5 ; 31.9 ; 32.1 ; 32.4
d) 50 ⇒ 49.5 ; 49.9 ; 50.1 ; 50.4
e) 67 ⇒ 66.5 ; 66.9 ; 67.1 ; 67.4
f) 71 ⇒ 70.5; 70.9 ; 71.1 ; 71.4
g) 88 ⇒ 87.5; 87.9 ; 88.1 ; 88.4
h) 95 ⇒ 94.5; 94.9 ; 95.1 ; 95.4
If the following number is within the range of 1 to 4 then round down.
<span>If the following number is within the range of 5 to 9 then round up.</span>
The <em>directional</em> derivative of
at the given point in the direction indicated is
.
<h3>How to calculate the directional derivative of a multivariate function</h3>
The <em>directional</em> derivative is represented by the following formula:
(1)
Where:
- Gradient evaluated at the point
.
- Directional vector.
The gradient of
is calculated below:
(2)
Where
and
are the <em>partial</em> derivatives with respect to
and
, respectively.
If we know that
, then the gradient is:
![\nabla f(r_{o}, s_{o}) = \left[\begin{array}{cc}\frac{s}{1+r^{2}\cdot s^{2}} \\\frac{r}{1+r^{2}\cdot s^{2}}\end{array}\right]](https://tex.z-dn.net/?f=%5Cnabla%20f%28r_%7Bo%7D%2C%20s_%7Bo%7D%29%20%3D%20%5Cleft%5B%5Cbegin%7Barray%7D%7Bcc%7D%5Cfrac%7Bs%7D%7B1%2Br%5E%7B2%7D%5Ccdot%20s%5E%7B2%7D%7D%20%5C%5C%5Cfrac%7Br%7D%7B1%2Br%5E%7B2%7D%5Ccdot%20s%5E%7B2%7D%7D%5Cend%7Barray%7D%5Cright%5D)
![\nabla f (r_{o}, s_{o}) = \left[\begin{array}{cc}\frac{3}{1+1^{2}\cdot 3^{2}} \\\frac{1}{1+1^{2}\cdot 3^{2}} \end{array}\right]](https://tex.z-dn.net/?f=%5Cnabla%20f%20%28r_%7Bo%7D%2C%20s_%7Bo%7D%29%20%3D%20%5Cleft%5B%5Cbegin%7Barray%7D%7Bcc%7D%5Cfrac%7B3%7D%7B1%2B1%5E%7B2%7D%5Ccdot%203%5E%7B2%7D%7D%20%5C%5C%5Cfrac%7B1%7D%7B1%2B1%5E%7B2%7D%5Ccdot%203%5E%7B2%7D%7D%20%5Cend%7Barray%7D%5Cright%5D)
![\nabla f (r_{o}, s_{o}) = \left[\begin{array}{cc}\frac{3}{10} \\\frac{1}{10} \end{array}\right]](https://tex.z-dn.net/?f=%5Cnabla%20f%20%28r_%7Bo%7D%2C%20s_%7Bo%7D%29%20%3D%20%5Cleft%5B%5Cbegin%7Barray%7D%7Bcc%7D%5Cfrac%7B3%7D%7B10%7D%20%5C%5C%5Cfrac%7B1%7D%7B10%7D%20%5Cend%7Barray%7D%5Cright%5D)
If we know that
, then the directional derivative is:
![\nabla_{\vec v} f = \left[\begin{array}{cc}\frac{3}{10} \\\frac{1}{10} \end{array}\right] \cdot \left[\begin{array}{cc}5\\10\end{array}\right]](https://tex.z-dn.net/?f=%5Cnabla_%7B%5Cvec%20v%7D%20f%20%3D%20%5Cleft%5B%5Cbegin%7Barray%7D%7Bcc%7D%5Cfrac%7B3%7D%7B10%7D%20%5C%5C%5Cfrac%7B1%7D%7B10%7D%20%5Cend%7Barray%7D%5Cright%5D%20%5Ccdot%20%5Cleft%5B%5Cbegin%7Barray%7D%7Bcc%7D5%5C%5C10%5Cend%7Barray%7D%5Cright%5D)

The <em>directional</em> derivative of
at the given point in the direction indicated is
. 
To learn more on directional derivative, we kindly invite to check this verified question: brainly.com/question/9964491