Reflect the quadrilateral across the line y=x

What equation can be used to find 150 percent of 500

kolbaska11 [484]

Answer:

750

Step-by-step explanation:

150 is bigger than 100 so we know the answer has to be bigger than 500. 150/100*500=150*5=750

8 0

3 years ago

Read 2 more answers

At a school with 100? students, 33 were taking? Arabic, 32 ?Bulgarian, and 40 Chinese. 9 students take only? Arabic, 12 take onl

Stels [109]

Answer: The answer is 4 and 32.

Step-by-step explanation: Let "A", "B" and "C" represents the set of students who were taking Arabic, Bulgarian and Chinese respectively.

The, according to the given information, we have

$n(A)=33,~~n(B)=32,~~n(C)=40,~~n(A\cap B)=14.$

Let 'p' represents the number of students who take all the three languages, then

$n(A\cap B\cap C)=p.$

Also,

$n(A)-n(A\cap B)-n(A\cap C)+n(A\cap B\cap C)=9\\\\\Rightarrow n(A\cap B)+n(A\cap C)=24+p~~~~~~~~~~~~~~(a),\\\\n(A\cap B)+n(B\cap C)=20+p~~~~~~~~~~~~~~(b),\\\\n(B\cap C)+n(A\cap C)=20+p~~~~~~~~~~~~~~~(c).$

From here, we get after subtracting equation(c) from (b) that

$n(A\cap B)=n(A\cap C)=14.$

Therefore,

$p=14+14-24=4,$ and from equation (a), we find

$n(B\cap C)=24-14=10.$

Thus,

$n(A\cap B\cap C)=4$ and

$n(A\cup B\cup C)=n(A)+n(B)+n(C)-n(A\cap B)-n(B\cap C)-n(A\cap C)+n(A\cap B\cap C)\\\\\Rightarrow n(A\cap B\cap C)=33+32+40-9-12-20+4\\\\\Rightarrow n(A\cap B\cap C)=68.$

Thus, the number of students who take all the three languages is 4 and the number of students who take none of the languages is 100-68 = 32.

5 0

3 years ago

Explain type i error and give an example. explain type ii error and give an example. what is the best way to reduce both kinds o

Leviafan [203]

Type I error says that we suppose that the null hypothesis exists rejected when in reality the null hypothesis was actually true.

Type II error says that we suppose that the null hypothesis exists taken when in fact the null hypothesis stood actually false.

<h3>What is Type I error and Type II error?</h3>

In statistics, a Type I error exists as a false positive conclusion, while a Type II error exists as a false negative conclusion.

Making a statistical conclusion still applies uncertainties, so the risks of creating these errors exist unavoidable in hypothesis testing.

The probability of creating a Type I error exists at the significance level, or alpha (α), while the probability of making a Type II error exists at beta (β). These risks can be minimized through careful planning in your analysis design.

Examples of Type I and Type II error

Type I error (false positive): the testing effect says you have coronavirus, but you actually don’t.
Type II error (false negative): the test outcome says you don’t have coronavirus, but you actually do.

To learn more about Type I and Type II error refer to:

brainly.com/question/17111420

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7 0

1 year ago

PQ=RQ <br> i’m looking for A in the problem

Naddik [55]

Answer:

i think the answer is 43 degrees but i dont know

8 0

3 years ago

Cual es la raiz cuadrada de 202

bezimeni [28]

Answer:

14.2126704036

Step-by-step explanation:

8 0

3 years ago