Can someone please tell me if these are correct?

Write p(x) = 21 + 24x + 6x2 in vertex form.

Helen [10]

To do this, complete the square:

p(x) = 21 + 24x + 6x2 => p(x) = 6x2 + 24x + 21

Rewrite the first 2 terms as

6(x^2 + 4x)

then you have p(x) = 6(x2 + 4x ) + 21

Now complete the square of x^2 + 4x:

p(x) = 6(x^2 + 4x + 4 - 4) + 21
= 6(x+2)^2 - 24 + 21

p(x) = 6(x+2)^2 - 3 this is in vertex form now.

We can read off the coordinates of the vertex from this: (-2, -3)

8 0

3 years ago

Julia went to the movies and bought one jumbo popcorn and two chocolate chip cookies for $5.00. Marvin went to the same movie an

hichkok12 [17]

X=price of one jumbo popcorn
y=price of one chocolate chip cookies

$5.00=$5.00(100 cts / $)=500 cts
$6.00=$6.00(100 cts / $)=600 cts

We suggest this system of equations:

x+2y=500
x+4y=600

we solve this system of equations by reduction method.

-(x+2y=500)
x+4y=600
----------------------
2y=100 ⇒ y=100/2=50

x+2y=500
x+2(50)=500
x+100=500
x=500-100
x=400

solution: one chocolate chip cookie cost 50 cts.

4 0

4 years ago

What is the square root of 144

kramer

The square root of 144 is 12

6 0

4 years ago

Read 2 more answers

Anyone plzzz this is due in an hour!!!! Will mark the brainliest

Crazy boy [7]

Answer:

C. Rectangle

Step-by-step explanation:

It will result in to a rectangle

6 0

3 years ago

medical tests. Task Compute the requested probabilities using the contingency table. A group of 7500 individuals take part in a

uysha [10]

Probabilities are used to determine the chances of an event

The probability that a person is sick is: 0.008
The probability that a test is positive, given that the person is sick is 0.9833
The probability that a test is negative, given that the person is not sick is: 0.9899
The probability that a person is sick, given that the test is positive is: 0.4403
The probability that a person is not sick, given that the test is negative is: 0.9998
A 99% accurate test is a correct test

(a) Probability that a person is sick

From the table, we have:

$\mathbf{Sick = 59+1 = 60}$

So, the probability that a person is sick is:

$\mathbf{Pr = \frac{Sick}{Total}}$

This gives

$\mathbf{Pr = \frac{60}{7500}}$

$\mathbf{Pr = 0.008}$

The probability that a person is sick is: 0.008

(b) Probability that a test is positive, given that the person is sick

From the table, we have:

$\mathbf{Positive\ and\ Sick=59}$

So, the probability that a test is positive, given that the person is sick is:

$\mathbf{Pr = \frac{Positive\ and\ Sick}{Sick}}$

This gives

$\mathbf{Pr = \frac{59}{60}}$

$\mathbf{Pr = 0.9833}$

The probability that a test is positive, given that the person is sick is 0.9833

(c) Probability that a test is negative, given that the person is not sick

From the table, we have:

$\mathbf{Negative\ and\ Not\ Sick=7365}$

$\mathbf{Not\ Sick = 75 + 7365 = 7440}$

So, the probability that a test is negative, given that the person is not sick is:

$\mathbf{Pr = \frac{Negative\ and\ Not\ Sick}{Not\ Sick}}$

This gives

$\mathbf{Pr = \frac{7365}{7440}}$

$\mathbf{Pr = 0.9899}$

The probability that a test is negative, given that the person is not sick is: 0.9899

(d) Probability that a person is sick, given that the test is positive

From the table, we have:

$\mathbf{Positive\ and\ Sick=59}$

$\mathbf{Positive=59 + 75 = 134}$

So, the probability that a person is sick, given that the test is positive is:

$\mathbf{Pr = \frac{Positive\ and\ Sick}{Positive}}$

This gives

$\mathbf{Pr = \frac{59}{134}}$

$\mathbf{Pr = 0.4403}$

The probability that a person is sick, given that the test is positive is: 0.4403

(e) Probability that a person is not sick, given that the test is negative

From the table, we have:

$\mathbf{Negative\ and\ Not\ Sick=7365}$

$\mathbf{Negative = 1+ 7365 = 7366}$

So, the probability that a person is not sick, given that the test is negative is:

$\mathbf{Pr = \frac{Negative\ and\ Not\ Sick}{Negative}}$

This gives

$\mathbf{Pr = \frac{7365}{7366}}$

$\mathbf{Pr = 0.9998}$

The probability that a person is not sick, given that the test is negative is: 0.9998

(f) When a test is 99% accurate

The accuracy of test is the measure of its sensitivity, prevalence and specificity.

So, when a test is said to be 99% accurate, it means that the test is correct, and the result is usable; irrespective of whether the result is positive or negative.