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Mama L [17]
3 years ago
15

Write these fractions in least common denominator2/5x+15y 1/2x+6y

Mathematics
1 answer:
Over [174]3 years ago
3 0
Look at deonomators

assuming that the deonomenators are 5x+15y and 2x+6y

find their LCM
factor

5x+15y=5(x+3y)

2x+6y=2(x+3y)

LCM=10(x+3y)=10x+30y

multiply 2/(5x+15y) by 2/2=4/(10x+30y)
multiply 1/(2x+6y) by 5/5=5/(10x+30y)

if we add them
9/(10x+30y)
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What is the volume of the cylinder below?
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3.14 * (18 : 2)² * 12 =

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7 0
3 years ago
Read 2 more answers
Charlie guesses that his dog weighs 34. 5 pounds. The dog actually weighs 32. 7 pounds. What is the percent error in Charlie’s g
expeople1 [14]

Percent error is the amount of error to actual value, in percent. The percent error in Charlie’s guess is approximately: Option D: 5.5%

<h3>How to calculate the percent error?</h3>

Suppose the actual value and the estimated values after the measurement are obtained. Then we have:

Error = Actual value - Estimated value

To calculate percent error, we will measure how much percent of actual value, the error is, in the estimated value.

\rm Percent \: Error = |\dfrac{Error}{Actual value}|\times 100 \\\\Percent \: Error = | \dfrac{\text{(Actual Value - Estimated Value)}}{Actual value}|\times 100 \\

(here |x| is such that it makes x non negative, thus, |-5| = 5, and |5| = 5)

For the given case, it is specified that:

Actual weight of dog = 32.7 pounds

Guessed weight of dog, by Charlie : 34.5 pounds.

Error = 32.7 - 34.5 = -1.8 pounds

Thus, percent error in Charlie's guess is calculated as:

\text{Percent Error} = |\dfrac{-1.8}{32.7}| \times 100 \approx 5.5\%

Hence, the percent error in Charlie’s guess is obtained approximately is given by: Option D: 5.5%

Learn more about percent error here:

brainly.com/question/25749180

3 0
2 years ago
What is the equation of the best-fitting regression line? Find this in two ways. First, using the regression analysis part of th
Lemur [1.5K]

Step-by-step explanation:

Regression analysis is used to infer about the relationship between two or more variables.

The line of best fit is a straight line representing the regression equation on a scatter plot. The may pass through either some point or all points or none of the points.

<u>Method 1:</u>

Using regression analysis the line of best fit is: y=\alpha +\beta x+e

Here <em>α </em>= intercept, <em>β</em> = slope and <em>e</em> = error.

The formula to compute the intercept is:

\alpha =\bar y-\beta \bar x

Here<em> </em>\bar y and \bar x are mean of the <em>y</em> and <em>x</em> values respectively.

\bar y=\frac{\sum y_{i}}{n} \\\bar x=\frac{\sum x_{i}}{n}

The formula to compute the slope is:

\beta =\frac{\sum (x-\bar x)(y - \bar y)}{\sum (x=\bar x)^{2}}

And the formula to compute the error is:

e=y-\alpha -\beta x

<u>Method 2:</u>

The regression line can be determined using the descriptive statistics mean, standard deviation and correlation.

The equation of the line of best fit is:

(y-\bar y)=r\frac{\sigma_{x}}{\sigma_{y}} (x-\bar x)

Here <em>r</em> = correlation coefficient = r=\frac{Cov (x,y)}{\sqrt{\sigma^{2}_{x}\sigma^{2}_{y}} }

\sigma_{x} and \sigma_{y} are standard deviation of <em>x</em> and <em>y</em> respectively.

\sigma_{x}=\frac{1}{n}\sum (x-\bar x)^{2} \\\sigma_{y}=\frac{1}{n}\sum (y-\bar y)^{2}

3 0
3 years ago
In the linear equation y=3x-4, -4 represents the slope
damaskus [11]
3 (3/1) represents the slope and -4 is the y-intercept
4 0
4 years ago
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