What is the average of 125 and 104

There are about 320 million people living in the United States. Of these, how many would you predict wear corrective lenses

tiny-mole [99]

Answer:

240 million

Step-by-step explanation:

Google said that three out of four people wear corrective lenses which is also 75%. So whats 75% out of 320 million? Half of 320 million is 160 million. Half of 160 million is 80 million, 160 million plus 80 million is 240 million.

8 0

3 years ago

Read 2 more answers

Write an equation of the line. y = _____ Use x as your variable.

muminat

Answer:

y= -2x+15

Step-by-step explanation:

5 0

3 years ago

This is a bonus question

Elena L [17]

Answer:

10,500

Step-by-step explanation:

See this as 2 rectangles: a box of water (28cm), and another box with the height you want (35cm)

Area of Rectangle = lwh

For the water;

50 x 30 x 28= 42000

As for the needed volume:

50 x 30 x 35 = 52500

To find how much more water, subtract the smaller volume from bigger volume.

10500 should be the final answer

3 0

2 years ago

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Multiply (6x+4y)(6x-4y)

MAXImum [283]

<h2>36x squared - 16y squared </h2>

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.