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aleksklad [387]
3 years ago
14

Solve for w. 1/3w + 5/6w - 2 = -w

Mathematics
2 answers:
Scorpion4ik [409]3 years ago
6 0

Answer: w=\frac{12}{13}

Step-by-step explanation:

To solve for w, we want to isolate the variable.

\frac{1}{3}w +\frac{5}{6}w-2=-w        [add both sides by 2 and w]

\frac{1}{3}w +\frac{5}{6}w+w=2           [convert to same denominator]

\frac{2}{6}w +\frac{5}{6}w+\frac{6}{6} w=2         [add]

\frac{13}{6} w=2                          [multiply both sides by 6/13]

w=\frac{12}{13}

Now we know that w=\frac{12}{13}.

Brrunno [24]3 years ago
4 0

Answer:

Step-by-step explanation:

1/3w + 5/6w - 2 = -w    Collect like terms on the left.

Before I do, I'm going to assume the question is (1/3)w + (5/6)w - 2 = - w

(1/3)w + (5/6)w - 2 = - w

 

1/3 + 5/6 = 2/6 + 5/6 = 7/6

(7/6)w - 2 = -w             Add w to both sides

(7/6)w + w - 2 = 0        Combine the left

(7/6)w + 6/6 w - 2 = 0

(13 / 6) w - 2 = 0          Add 2 to both sides

(13/ 6) w = 2                 Divide by 13/6

w = (2/1 ) ÷ (13/6)          Invert the denominator and multiply

w = 2/1 * 6/13

w = 12/13    

             

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Answer:

a) r=\frac{4(333)-(200)(5.37)}{\sqrt{[4(12000) -(200)^2][4(9.3501) -(5.37)^2]}}=0.9857  

The correlation coefficient for this case is very near to 1 so then we can ensure that we have linear correlation between the two variables

b) m=\frac{64.5}{2000}=0.03225  

Now we can find the means for x and y like this:  

\bar x= \frac{\sum x_i}{n}=\frac{200}{4}=50  

\bar y= \frac{\sum y_i}{n}=\frac{5.37}{4}=1.3425  

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So the line would be given by:  

y=0.3225 x -0.27  

Step-by-step explanation:

Part a

The correlation coeffcient is given by this formula:

r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}  

For our case we have this:

n=4 \sum x = 200, \sum y = 5.37, \sum xy = 333, \sum x^2 =12000, \sum y^2 =9.3501  

r=\frac{4(333)-(200)(5.37)}{\sqrt{[4(12000) -(200)^2][4(9.3501) -(5.37)^2]}}=0.9857  

The correlation coefficient for this case is very near to 1 so then we can ensure that we have linear correlation between the two variables

Part b

m=\frac{S_{xy}}{S_{xx}}  

Where:  

S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i)}{n}  

S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}  

With these we can find the sums:  

S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}=12000-\frac{200^2}{4}=2000  

S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i){n}}=333-\frac{200*5.37}{4}=64.5  

And the slope would be:  

m=\frac{64.5}{2000}=0.03225  

Now we can find the means for x and y like this:  

\bar x= \frac{\sum x_i}{n}=\frac{200}{4}=50  

\bar y= \frac{\sum y_i}{n}=\frac{5.37}{4}=1.3425  

And we can find the intercept using this:  

b=\bar y -m \bar x=1.3425-(0.03225*50)=-0.27  

So the line would be given by:  

y=0.3225 x -0.27  

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