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zzz [600]
3 years ago
5

What is 1 7/10 divided by 3/5 ?

Mathematics
2 answers:
charle [14.2K]3 years ago
6 0
The first step is to change the mixed number into an improper fraction.
1 7/10 = 17/10
(17/10) / (3/5) =
(17/10) * (5/3) = (change the division to a multiplication by the reciprocal.
17/6 = 2 5/6
VMariaS [17]3 years ago
5 0
The answer is: 17/6 ....
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Can you help me please ​
Olenka [21]

Answer:

log_372 = 3.8928

Step-by-step explanation:

Given

log_38 = 1.8928

Required

Evaluate log_372

We have:

log_372 = log_3(8 *9)

Apply law of logarithm

log_372 = log_38 +log_39

Express 9 as 3^2

log_372 = log_38 +log_33^2

Evaluate the exponents

log_372 = log_38 +2log_33

log_33 = 1.

So:

log_372 = log_38 + 2 * 1

log_372 = log_38 + 2

Substitute log_38 = 1.8928

log_372 = 1.8928 + 2

log_372 = 3.8928

5 0
2 years ago
Given the function h(x) = -x² - 2x + 3, determine the average rate of change of
tino4ka555 [31]
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3 0
1 year ago
5. In the figure, . Solve for . Show your work.
natima [27]

Answer:

15

Step-by-step explanation:

6/10=9/x

cross multiply

6x=9*10

6x=90

x=90/6x=15

3 0
3 years ago
Suppose the system of linear equations has infinitely many solutions. What is the value of y for the second equation?
Otrada [13]
I believe it would be 4

This is because when divided by 3, 3x+12y=3 turns into x+4y=3
6 0
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Read 2 more answers
A research team hypothesizes that setting weekly scheduled online interactions versus not setting such interactions can boost th
leva [86]

Answer:

Type I error occurs when the null hypothesis, H0, is rejected, although it is true.

Here the null hypothesis, H0 is:

H0: Setting weekly scheduled online interactions will boost the well being of people who are living on their own during the stay at home order.

a) A Type I error would be committed if the researchers conclude that setting weekly scheduled online interactions will not boost the well being of people who are living on their own during the stay at home order, but in reality it will

b) Two factors affecting type I error:

1) When the sample size, n, is too large it increases the chances of a type I error. Thus, a sample size should be small to decrease type I error.

2)A smaller level of significance should be used to decrease type I error. When a larger level of significance is used it increases type I error.

7 0
3 years ago
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