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3 years ago

I have 4 questions (please help) IM BEGGING YOU i need help! please!!!!

1 answer:

6 0

1) 18h = 252
You divide each side by 18, so you can get "h" alone on a side, and its value on the other side of the equation.
(18h)/18 = 252/18
h = 14 (Answer C)

2) 31d = 186.
Same Thing, you divide each side by 31, so you can get "d" alone on a side, and its value on the other side of the equation.
(31d)/31 = 186/31
d= 6 (Answer B)

3) 55c = 385
Again, same thing, You divide each side by 55, so you can get "c" alone on a side, and its value on the other side of the equation.
(55c)/55 = 385/55
c = 7 (Answer B)

4) 50w = 1050
You divide each side by 50, so you can get "w" alone on a side, and its value on the other side of the equation.
(50w)/50 = 1050/50
w=21 (Answer A)

As you can notice, they all follow the same steps: dividing by the coefficient of the variable both sides, so you can the variable alone on the first side of the equation, and its value on the second side.

Hope this Helps! :)

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Step-by-step explanation:

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a) Let us determine the sum

$\sum x_i= 100+200+300+400+490=1490$

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Now we can determine $S_x_x, S_x_y, S_y_y$

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$S_x_y = \sum x_i y_i -\frac{(\sum x_i)(\sum y_i) }{n} \\\\$

$653830 - \frac{1490 \times 1978 }{5} = 64386$

$S_y_y = \sum y_i^2-\frac{(\sum y_i)^2 }{n} = 82750-\frac{1978^2}{5} \\\\= 45007.2$

The estimate b of the slope β is the ratio of $S_x_y$ and $S_x_x$

$b = \frac{S_x_y}{S_x_x}$

$\frac{64386}{96080} = 0.67$

The mean is the sum of all value divide by number of values

$\bar x= \frac{\sum x_i}{n} \\\\= \frac{100+200+300+400+490}{5} \\\\= \frac{1490}{5} = 298$

$\bar y= \frac{\sum y_i}{n} \\\\= \frac{237+350+419+465+507}{5} \\\\= \frac{1978}{5} = 395.6$

The estimate a of the intercept is

$a = \bar y - b \bar x$

$= 395.6 - 0.69 \times 298\\= 195.9$

General least square equation;

$\bar y = \alpha + \beta x$

replace alpha by a = 3 and beta by b = 0.67 in general least equation

y = a + bx

195.9 + 0.67x

<em>Scatter plot is shown in the attached file</em>

x is on the horizontal axis

y is n the vertical axis

The degree of freedom of regression is 1

because we use one variable s predictor variable

$d_f_R = 1$

The degree of freedom of error is the sample size n decrease by 2

$d_f_E =n-2= 5 - 2=3$

Total df is equal to the sum of seperate degree of freedom dfR and dfE

total df = 1 +3 4

$SSR = \frac{(S_x_y)^2}{S_x_x} = \frac{64386^2}{96080} \\\\= 43146.9296$

Total SS =Syy= 45007.2

SSE + Total SS = SSR

= 45007.2 - 43146.9296

= 1860.2705

7 0

3 years ago