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3 years ago

How do I convert 82.1, 7.3, 9.3 in a fraction form

Mathematics

1 answer:

nalin [4]3 years ago

5 0

Answer:

Step-by-step explanation:

82.1 = 82 1/10 (thats 82 and 1/10) or 821/10 (if you dont want a mixed number)

7.3 = 7 3/10 or 73/10

9.3 = 9 3/10 or 93/10

if there is 1 number to the right of the decimal, put that number over 10....not the whole number, just the number to the right of the decimal. Leave the number to the left of the decimal alone.

if there were 2 numbers to the right of the decimal, then put those two numbers over 100.

example :

3.43 = 3 43/100

2.76 = 2 76/100

if there were 3 numbers to the right of the decimal, put those 3 numbers over 1000

example :

2.347 = 2 347/1000

3.679 = 3 679/1000

you understand ?

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PLS ANSWER PLS IM DESPRATE WILL MARK BRAINLIEST 18 POINTS

Jlenok [28]

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3 years ago

Select all the true statements

Doss [256]

The true statements are;

1) AB + BC = AC

Length of BC = |6 - 1|

2) ∠JMK = 50°

∠KML = 35°

<h3>How to Interpret Number Line intervals?</h3>

1) From the given number line interval, we can deduce the interpretation as follows;

AB + BC = AC

Length of BC = 5 units or |6 - 1|

Length of B = 3 Units

2) We can see that ∠JML is an angle triangle. Thus, ∠JML = 85°. Thus;

6x + 2 + 4x + 3 = 85

10x + 5 = 85

10x = 85 - 5

10x = 80

x = 80/10

x = 8°

Thus;

∠JMK = 6(8) + 2

∠JMK = 50°

∠KML = 85° - 50°

∠KML = 35°

Read more about Number Line Intervals at; brainly.com/question/27998235

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2 years ago

Cálculo da equação 5 (x+1)=3 (x-1)

Lana71 [14]

Answer:

x=−4

Step-by-step explanation:

5(x+1)=3(x−1)

5x+5=3(x−1)

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3 years ago

The admissions officer for Clearwater College developed the following estimated regression equation relating the final college G

emmainna [20.7K]

A null hypothesis illustrates that two variables in the hypothesis have no statistical significance.

The null hypothesis is: $\mathbf{H_0 : \beta = 0}$

The regression equation is given as:

$\mathbf{\bar y = -1.41 + 0.02351x_1 + 0.0048x_2}$

The variables are: $\mathbf{x_1}$ and $\mathbf{x_2}$

The null hypothesis states that, there is no statistical significance between $\mathbf{x_1}$ and $\mathbf{x_2}$ .

This is represented as:

$\mathbf{H_0 : \beta = 0}$

Hence, the null hypothesis is: $\mathbf{H_0 : \beta = 0}$