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dangina [55]
3 years ago
14

Describe the effect of the transformation (x,y) to (x,7y)

Mathematics
1 answer:
elena-s [515]3 years ago
5 0
The correct answer is B!
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Im sped Help MEEEEE PLEASEEE
lana66690 [7]

Answer:

2x^4

-x^3 + 3x^2 + 2x + 4

5x^2 + 5x + 5

-3x + 10

22

Step-by-step explanation:

find the highest exponent of each polynomials:

22=> 0 degree

-3x(equals to -3x^1) + 10=> 1st degree

5x^2 + 5x + 5=> 2nd degree

-x^3 + 3x^2 + 2x + 4=> 3rd degree

2x^4=> 4th degree

7 0
3 years ago
Can someone please answer this asap (50 Points)<br> Graph the following piecewise function.
kiruha [24]

answer D for the equation

8 0
3 years ago
Read 2 more answers
Heidi earns $11.50 per hour plus a bonus of $105 for the week. Her goal is to earn $650 for the week. Which equation
Stells [14]

Answer:

48 hours

Step-by-step explanation:

$650 - $105 = $545

$545 ÷ $11.50 = 47.39 = 48 hours (Rounded)

6 0
3 years ago
Two angles of a triangle have the same measure and the third one is 18 degrees greater than the measure of each of the other two
kvv77 [185]

Answer:

72°

Step-by-step explanation:

Let the 2 equal angles be x then the third angle is x + 18

The sum of the 3 angles in a triangle = 180°, thus

x + x + x + 18 = 180, that is

3x + 18 = 180 ( subtract 18 from both sides )

3x = 162 ( divide both sides by 3 )

x = 54

Hence

the largest angle = x + 18 = 54 + 18 = 72°

4 0
3 years ago
The director of admissions at Kinzua University in Nova Scotia estimated the distribution of student admissions for the fall sem
wariber [46]

Answer:

In order to calculate the expected value we can use the following formula:  

E(X)=\sum_{i=1}^n X_i P(X_i)  

And if we use the values obtained we got:  

E(X)=(1060*0.5) +(1400*0.1) +(1620*0.4)=1318  

Step-by-step explanation:

Let X the random variable that represent the number of admisions at the universit, and we have this probability distribution given:

X        1060   1400    1620

P(X)     0.5      0.1        0.4

In statistics and probability analysis, the expected value "is calculated by multiplying each of the possible outcomes by the likelihood each outcome will occur and then summing all of those values".

The variance of a random variable Var(X) is the expected value of the squared deviation from the mean of X, E(X).

And the standard deviation of a random variable X is just the square root of the variance.  

In order to calculate the expected value we can use the following formula:  

E(X)=\sum_{i=1}^n X_i P(X_i)  

And if we use the values obtained we got:  

E(X)=(1060*0.5) +(1400*0.1) +(1620*0.4)=1318  

3 0
3 years ago
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