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3 years ago

What is 699,900 rounded to the nearest thousand

Mathematics

2 answers:

Rus_ich [418]3 years ago

6 0

When you round 699,900 to the nearest hundred, you get 700,00.

vampirchik [111]3 years ago

3 0

Answer:

The answer is $"700,000"$ .

Step-by-step explanation:

When you're rounding up to the "Nearest" all you have to do is find for the thousands place then look to the right of the number. If it's 4 or down, round down. but If it's 5 or up, round up. It's as simple as that. The number to the right of the thousands is 9, so we round up 700,000.

And that will be you're answer!

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Simplify the expression (2h+1)(8)

Elza [17]

Answer:

$16h+8$

Step-by-step explanation:

$(2h+1)(8)$

Multiply 8 with 2h and 1

$16h+8$

8 0

2 years ago

Given: Triangle ABC, mmBC=24 cm, line segment AL- < bisector

Furkat [3]

The value of line AL is 21. 51cm

<h3>How to determine the length</h3>

To find line AL,

Using

Sin α = opposite/ hypotenuse to find line AB

Sin 90 = x/ 24

1 = x/24

Cross multiply

x = 24cm

Now, let's find line AC

Sin angle B = line AC/24

Note that to find angle B

angle A + angle B + angle C = 180

But angle B = 2 Angle A

x + 2x + 90 = 180

3x + 90 = 180

3x = 180-90

x = 30°

Angle B = 2 × 30 = 60°

Sin 60 = x/ 24

0. 8660 = x/24

Cross multiply

x = 24 × 0. 8660

x = 20. 78cm

We have the angle of A in the given triangle to be divide into two by the bisector, angle A = 15°

To find line AL, we use

Cos = adjacent/ line AL

Cos 15 = 20. 78/ line AL

Line AL = 20. 78/ cos 15

Line AL = 20. 78 / 0. 9659

Line AL = 21. 51 cm

Thus, the value of line AL is 21. 51cm

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6 0

1 year 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.

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2 years ago

Name some underrated animes i should watch.

Elena L [17]

Answer:

one i have is samurai flamenco

Step-by-step explanation:

its cool to me

8 0

2 years ago

Read 2 more answers

When taking a sample from a population, which of the following is true?

salantis [7]

Answer:

The larger the number of items in the sample, the more closely the distribution of sample items will follow a bell-shaped curve

Step-by-step explanation:

The question is about the distribution of the sample

The sampling distribution, also called the distribution of the sample mean is the distribution for many samples drawn form population at random for large sizes.

As per central limit theorem, if samples of sufficiently large size to represent the population is drawn from the population, the sample means of all sample will follow a normal distribution and hence bell shaped.

So from the options we say a is incorrect because not always

b is incorrect because there is no mention about the chance.

c is incorrect because when we use sample variance we use t test

Option d is correct.

The larger the number of items in the sample, the more closely the distribution of sample items will follow a bell-shaped curve

7 0

2 years ago