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Nat2105 [25]
2 years ago
7

What are the y-intercept and the asymptote of g(x) = 2x – 3?

Mathematics
1 answer:
natta225 [31]2 years ago
6 0

Answer:

no asymptote

y-intercept is -3 (or, written as a point: (0,-3))

Step-by-step explanation:

g(x) = 2x -3 is a linear function in the form y = mx +b.

This is called slope-intercept form. g(x) is a line, with slope 2 and y-intercept -3.

You might be interested in
Write the equation, in the slope-intercept form, for the line shown in the graph below:
AysviL [449]

Answer:

y = -3x

Step-by-step explanation:

Slope is -3

8 0
3 years ago
What are the roots of the quadratic equation 2x2+7x+4=0? Select all that apply.
skad [1K]

Answer:

option A and B

x=\frac{-7+\sqrt{17}} {4}

and

x=\frac{-7-\sqrt{17}} {4}

Step-by-step explanation:

we have

2x^2+7x+4=0

The formula to solve a quadratic equation of the form

ax^{2} +bx+c=0

is equal to

x=\frac{-b\pm\sqrt{b^{2}-4ac}} {2a}

in this problem we have

2x^2+7x+4=0

so

a=2\\b=7\\c=4

substitute in the formula

x=\frac{-7\pm\sqrt{7^{2}-4(2)(4)}} {2(2)}

x=\frac{-7\pm\sqrt{17}} {4}

so

x=\frac{-7+\sqrt{17}} {4}

and

x=\frac{-7-\sqrt{17}} {4}

7 0
3 years ago
The ability to examine the variability of a solution due to changes in the formulation of a problem is an important part of the
PilotLPTM [1.2K]

Answer:

Sensitivity Analysis

Step-by-step explanation:

Sensitivity analysis is the study of how the uncertainty in the output of a mathematical model or system (numerical or otherwise) can be divided and allocated to different sources of uncertainty in its inputs.

4 0
3 years ago
Suppose that you are given a bag containing n unbiased coins. You are told that n-1 of these coins are normal, with heads on one
gladu [14]

Answer:

The (conditional) probability that the coin you chose is the fake coin is 2/(1 + n)

Step-by-step explanation:

Given

Total unbiased coin = n

Normal coins =n - 1

Fake = 1

The (conditional) probability that the coin you chose is the fake coin is represented by

P(Fake | Head)

And it's calculated as follows;

P(Fake | Head) = P(Fake, Head) ÷ P(Head) ----- (1)

Where P(Fake, Head) = P(Fake) * P(Head | Fake)

P(Fake) = 1/n --- because only one is fake

P(Head | Fake) = n/n because all coins (including the fake) have head

So, P(Fake, Head) = P(Fake) * P(Head | Fake) becomes

P(Fake, Head) = 1/n * n/n

P(Fake, Head) = 1/n

P(Head) is calculated by

P(Fake) * P(Head | Fake) + P(Normal) * P(Head | Normal)

P(Fake) * P(Head | Fake) = P(Fake, Head) = 1/n (as calculated above)

P(Normal) * P(Head | Normal) = ½ * (n - 1)/n ----- considering that the coin also has a tail with equal probability as that of the head.

Going back to (1)

P(Fake | Head) = P(Fake, Head) ÷ P(Head) becomes

P(Fake | Head) = (1/n) ÷ ((1/n) + (½(n-1)/n))

= (1/n) ÷ ((1/n) + (½(n-1)/n))

= (1/n) ÷ (1/n + (n - 1)/2n)

= (1/n) ÷ (2 + n - 1)/(2n)

= (1/n) ÷ (1 + n)/(2n)

= (1/n) * (2n)/(1 + n)

= 2/(1 + n)

Hence, the (conditional) probability that the coin you chose is the fake coin is 2/(1 + n)

5 0
3 years ago
I need to know how to do this step my step and the answer
MissTica
You can use the calculator or 0^2 is 0 x -3 =0 +7 (0) -4 =-4
5 0
4 years ago
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