It would be arrow
Because that is the right answer
The answer is a = 
Step-by-step explanation:
<em>1. Convert the mixed fraction to an improper fraction</em>
To find the numerator, multiply the denominator by the whole number and add the numerator to it.
The denominator remains the same.
So, 2
will be 
<em>2. Now the equation is,</em>
a -
a =
+
a
<em>3. Take LCM on both sides. </em>
For the left side, multiply the first fraction by
and multiply the second fraction by 
a -
a = 
<em>4. Solve by making a the subject</em>
= 
= 
=10+8a
= 10 + 8a
a = 2(10 + 8a)
a = 20 + 16a
a-16a = 20
-15a = 20
a = 
a = 
Therefore, the answer is a = 
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Answer:
a d and e
Step-by-step explanation:
none
Step-by-step explanation:
A rectangle: P=2l+2w or P=2(l+w) (same formula written differently)
50=2x17+2w
50=34+2w
2w=50-34
2w=16
w=16÷2=8
Since it says twice as wide then we will multiply w with 2
2xW
2x8=16 which is the width of the 2nd rectangle
Hope this helps :)
Answer:
a) 0.0853
b) 0.0000
Step-by-step explanation:
Parameters given stated that;
H₀ : <em>p = </em>0.6
H₁ : <em>p = </em>0.6, this explains the acceptance region as;
p° ≤
=0.63 and the region region as p°>0.63 (where p° is known as the sample proportion)
a).
the probability of type I error if exactly 60% is calculated as :
∝ = P (Reject H₀ | H₀ is true)
= P (p°>0.63 | p=0.6)
where p° is represented as <em>pI</em><em> </em>in the subsequent calculated steps below
= P ![[\frac{p°-p}{\sqrt{\frac{p(1-p)}{n}}} >\frac{0.63-p}{\sqrt{\frac{p(1-p)}{n}}} |p=0.6]](https://tex.z-dn.net/?f=%5B%5Cfrac%7Bp%C2%B0-p%7D%7B%5Csqrt%7B%5Cfrac%7Bp%281-p%29%7D%7Bn%7D%7D%7D%20%3E%5Cfrac%7B0.63-p%7D%7B%5Csqrt%7B%5Cfrac%7Bp%281-p%29%7D%7Bn%7D%7D%7D%20%7Cp%3D0.6%5D)
= P ![[\frac{p°-0.6}{\sqrt{\frac{0.6(1-0.6)}{500}}} >\frac{0.63-0.6}{\sqrt{\frac{0.6(1-0.6)}{500}}} ]](https://tex.z-dn.net/?f=%5B%5Cfrac%7Bp%C2%B0-0.6%7D%7B%5Csqrt%7B%5Cfrac%7B0.6%281-0.6%29%7D%7B500%7D%7D%7D%20%3E%5Cfrac%7B0.63-0.6%7D%7B%5Csqrt%7B%5Cfrac%7B0.6%281-0.6%29%7D%7B500%7D%7D%7D%20%5D)
= P ![[Z>\frac{0.63-0.6}{\sqrt{\frac{0.6(1-0.6)}{500} } } ]](https://tex.z-dn.net/?f=%5BZ%3E%5Cfrac%7B0.63-0.6%7D%7B%5Csqrt%7B%5Cfrac%7B0.6%281-0.6%29%7D%7B500%7D%20%7D%20%7D%20%5D)
= P [Z > 1.37]
= 1 - P [Z ≤ 1.37]
= 1 - Ф (1.37)
= 1 - 0.914657 ( from Cumulative Standard Normal Distribution Table)
≅ 0.0853
b)
The probability of Type II error β is stated as:
β = P (Accept H₀ | H₁ is true)
= P [p° ≤ 0.63 | p = 0.75]
where p° is represented as <em>pI</em><em> </em>in the subsequent calculated steps below
= P ![[\frac{p°-p} \sqrt{\frac{p(1-p)}{n} } }\leq \frac{0.63-p}{\sqrt{\frac{p(1-p)}{n} } } | p=0.75]](https://tex.z-dn.net/?f=%5B%5Cfrac%7Bp%C2%B0-p%7D%20%5Csqrt%7B%5Cfrac%7Bp%281-p%29%7D%7Bn%7D%20%7D%20%7D%5Cleq%20%5Cfrac%7B0.63-p%7D%7B%5Csqrt%7B%5Cfrac%7Bp%281-p%29%7D%7Bn%7D%20%7D%20%7D%20%7C%20p%3D0.75%5D)
= P ![[\frac{p°-0.6} \sqrt{\frac{0.75(1-0.75)}{500} } }\leq \frac{0.63-0.75}{\sqrt{\frac{0.75(1-0.75)}{500} } } ]](https://tex.z-dn.net/?f=%5B%5Cfrac%7Bp%C2%B0-0.6%7D%20%5Csqrt%7B%5Cfrac%7B0.75%281-0.75%29%7D%7B500%7D%20%7D%20%7D%5Cleq%20%5Cfrac%7B0.63-0.75%7D%7B%5Csqrt%7B%5Cfrac%7B0.75%281-0.75%29%7D%7B500%7D%20%7D%20%7D%20%5D)
= P![[Z\leq\frac{0.63-0.75}{\sqrt{\frac{0.75(1-0.75)}{500} } } ]](https://tex.z-dn.net/?f=%5BZ%5Cleq%5Cfrac%7B0.63-0.75%7D%7B%5Csqrt%7B%5Cfrac%7B0.75%281-0.75%29%7D%7B500%7D%20%7D%20%7D%20%5D)
= P [Z ≤ -6.20]
= Ф (-6.20)
≅ 0.0000 (from Cumulative Standard Normal Distribution Table).