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natka813 [3]
3 years ago
6

The measure of one of the acute angles in a right triangle is given. find the measure of the other acute angle

Mathematics
1 answer:
EleoNora [17]3 years ago
5 0
The sum of angles in a triangle is 180 degrees. In a right angle triangle one angle will be 90 degrees. And if one of the acute angles is already know then just minus 90 degrees and the known acute angle from 180 degrees to find the other acute angle.

180-90-known acute angle = unknown acute angle
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A researcher wishes to find out shearer givinh a student 1 million in cash will improve or ruin the students grades in school
arlik [135]
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Papessa [141]
3/4 = x / 340....3 to 4 students = x to 340 students
cross multiply
(4)(x) = (3)(340)
4x = 1020
x = 1020/4
x = 255 <==

or this way.....

3 out of 4 students.....3/4 = 75%
so 75% of 340 = 0.75(340) = 255 <=
4 0
4 years ago
Use the Counting Principle to find the probability. Choosing the 7 winning lottery numbers when the numbers are chosen at random
frozen [14]

Answer:   120

<u>Step-by-step explanation:</u>

Since the order of the numbers doesn't matter we can use the formula:

\dfrac{n!}{r!(n-r)!}\quad \text{where n is the quantity of items and r is the quantity chosen}\\\\\text{In this problem, there are 10 numbers (n = 10) and 7 to be chosen (r = 7)}\\\\_{10}C_{7}=\dfrac{10!}{7!(10-7)!}\\\\.\qquad=\dfrac{10!}{7!3!}\\\\.\qquad=\dfrac{10\times 9\times 8\times 7!}{7!\times 3\times 2\times 1}\\\\.\qquad=10\times 3\times 4\\\\.\qquad=120

7 0
3 years ago
Read 2 more answers
Suppose each of the following data sets is a simple random sample from some population. For each dataset, make a normal QQ plot.
adell [148]

Answer:

a) For this case the histogram is not too skewed and we can say that is approximately symmetrical so then we can conclude that this dataset is similar to a normal distribution

b) For this case the data is skewed to the left and we can't assume that we have the normality assumption.

c) This last case the histogram is not symmetrical and the data seems to be skewed.

Step-by-step explanation:

For this case we have the following data:

(a)data = c(7,13.2,8.1,8.2,6,9.5,9.4,8.7,9.8,10.9,8.4,7.4,8.4,10,9.7,8.6,12.4,10.7,11,9.4)

We can use the following R code to get the histogram

> x1<-c(7,13.2,8.1,8.2,6,9.5,9.4,8.7,9.8,10.9,8.4,7.4,8.4,10,9.7,8.6,12.4,10.7,11,9.4)

> hist(x1,main="Histogram a)")

The result is on the first figure attached.

For this case the histogram is not too skewed and we can say that is approximately symmetrical so then we can conclude that this dataset is similar to a normal distribution

(b)data = c(2.5,1.8,2.6,-1.9,1.6,2.6,1.4,0.9,1.2,2.3,-1.5,1.5,2.5,2.9,-0.1)

> x2<- c(2.5,1.8,2.6,-1.9,1.6,2.6,1.4,0.9,1.2,2.3,-1.5,1.5,2.5,2.9,-0.1)

> hist(x2,main="Histogram b)")

The result is on the first figure attached.

For this case the data is skewed to the left and we can't assume that we have the normality assumption.

(c)data = c(3.3,1.7,3.3,3.3,2.4,0.5,1.1,1.7,12,14.4,12.8,11.2,10.9,11.7,11.7,11.6)

> x3<-c(3.3,1.7,3.3,3.3,2.4,0.5,1.1,1.7,12,14.4,12.8,11.2,10.9,11.7,11.7,11.6)

> hist(x3,main="Histogram c)")

The result is on the first figure attached.

This last case the histogram is not symmetrical and the data seems to be skewed.

7 0
3 years ago
Need help asap please!!!
weeeeeb [17]

Answer:15

Step-by-step explanation: 7 and a half times 2 is 15

6 0
3 years ago
Read 2 more answers
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