Answer:
15) <u><em>y= 1/2 + 3.75</em></u>
16) <u><em>y = x</em></u>
Step-by-step explanation:
For #15)
<em>Equation used: y=mx+b ; Slope: y₂ - y₁ / x₂ - x₁</em>
1) First, you need to pick any 2 points on the graph. I'll use (6,3) and (8,4).
2.1) Then you'll use the <em>slope </em>equation to find the slope (m) of your equation.
(y) ~ 4 - 3 = 1
(x) ~ 8 - 6 = 2
Slope= 1/2
3) So from the look of the answers, the y here is 3.75 so you can trust that.
4) The final equation is <u><em>y= 1/2 + 3.75</em></u>
<u><em /></u>
For #16)
Use the same steps as #15. You can still choose whatever points/plots you want. Ima use (5,4) and (6,5).
(y) ~ 4 - 3 = 1
(x) ~ 6 - 5 = 1
slope= 1 or x
Answer: y=x
<em>Your welcome for the answer! <3</em>
F(x) = 16ˣ
A. g(x) = 8(2ˣ)
g(x) = (2³)(2ˣ)
g(x) = 2ˣ⁺³
The answer is not A.
B. g(x) = 4096(16ˣ⁻³)
g(x) = (16³)(16ˣ⁻³)
g(x) = 16ˣ
The answer is B.
C. g(x) = 4(4ˣ)
g(x) = 4ˣ⁺¹
The answer is not C.
D. g(x) = 0.0625(16ˣ⁺¹)
g(x) = (16⁻¹)(16ˣ⁺¹)
g(x) = 16ˣ
The answer is D.
E. g(x) = 32(16ˣ⁻²)
g(x) = (2⁵)(2⁴ˣ⁻⁸)
g(x) = 2(⁴ˣ⁻³)
The answer is not E.
F. g(x) = 2(8ˣ)
g(x) = 2(2³ˣ)
g(x) = 2³ˣ⁺¹
The answer is not F.
The answer is B and D.
Using a trigonometric equation, it is found that it will take 2.28 minutes until the two trains are first equidistant from the child.
<h3>What is the distance of each train to the child?</h3>
The distance of the first train is:
The distance of the second train is:
<h3>When are the trains equidistant to the child?</h3>
When 
, hence:
The following substitution is made:
Hence:
Which is a quadratic equation with coefficients 
, hence:
Then, applying the trigonometric equation, considering that 
due to the range of the cosine function:
It will take 2.28 minutes until the two trains are first equidistant from the child.
You can learn more about trigonometric equations at brainly.com/question/2088730
Answer:
6nx + 7p – 14p + 2nx – 6x
= 8nx -7p = 6x
answer is A.
8nx – 7p – 6x
Step-by-step explanation:
Answer:
Type I: 1.9%, Type II: 1.6%
Step-by-step explanation:
given null hypothesis
H0=the individual has not taken steroids.
type 1 error-falsely rejecting the null hypothesis
⇒ actually the null hypothesis is true⇒the individual has not taken steroids.
but we rejected it ⇒our prediction is the individual has taken steroids.
typr II error- not rejecting null hypothesis when it has to be rejected
⇒actually null hypothesis is false ⇒the individual has taken steroids.
but we didnt reject⇒the individual has not taken steroids.
let us denote
the individual has taken steroids by 1
the individual has not taken steroids.by 0
predicted
1 0
actual 1 98.4% 1.6%
0 1.9% 98.1%
so for type 1 error
actual-0
predicted-1
therefore from above table we can see that probability of Type I error is 1.9%=0.019
so for type II error
actual-1
predicted-0
therefore from above table we can see that probability of Type I error is 1.6%=0.016
