All categories

3 years ago

HELP EASY 30 POINTS!! PLUS BRAINLIEST !!!!!

Mathematics

2 answers:

KonstantinChe [14]3 years ago

8 0

1500+4.8x=1860

Minus 1500 and divide by 4.8 to get 75 I’m not sure if it’s true so don’t quote me on it

Tamiku [17]3 years ago

5 0

Answer:

Step-by-step explanation:

The formula for simple interest is expressed as

I = PRT/100

Where

I is the interest

P is the principal

R is the rate in percentage

The simple interest is earned only on the principal and not on compounded earnings

From the information given

P = $1500

R = 4.8%

Since she wants a total amount of $1,860 after a number of years, it means the interest on her principal will be 1860 - 1500 = $360

So we would solve for the number of years it will take to earn $360 interest. Therefore

360 = (1500 × 4.8 × t)/100

72t =360

t = 360/72 = 5

It will take 5 years

You might be interested in

jazz was 43 inches tall.Eighteen months later,she was 52 inches tall.determine the constant rate of change for jaz's height.

klasskru [66]

I got 6.5 inches per month I hope this helps

7 0

3 years ago

Does anyone know the answer to this problem?

Mariana [72]

The regression equation is y = 16.585x - 639.769 and the linear correlation coefficient indicates a strong linear relationship

<h3>How to determine the regression equation?</h3>

To do this, we make use of a statistical calculator;

Using the statistical calculator, we have the following summary:

Sum of X = 554
Sum of Y = 4070
Mean X = 69.25
Mean Y = 508.75
Sum of squares (SSX) = 725.5
Sum of products (SP) = 12032.5
Correlation coefficient, r = 0.9768

The regression equation is

ŷ = bx + a

Where:

b = SP/SSX = 12032.5/725.5 = 16.58511

a = MY - bMX = 508.75 - (16.59*69.25) = -639.76912

Hence, the regression equation is y = 16.585x - 639.769

<h3>The number of cans sold at 90 degrees F</h3>

This means that"

x = 90

So, we have:

y = 16.585 * 90 - 639.769

Evaluate

y = 852.881

Approximate

y = 853

Hence, 853 cans were sold at 90 degrees F

<h3>The linear correlation coefficient</h3>

In (a), we have:

r = 0.9768

This means that the linear correlation coefficient is 0.9768

<h3>The conclusion</h3>

We have:

r = 0.9768

The above value is closer to 1 because

|r| > 0.9

i.e.

0.9768 > 0.9

Hence, the linear correlation coefficient indicates a strong linear relationship