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hjlf
3 years ago
8

Divide 1.20m in the ratio 2:3:4 what's the answer

Mathematics
1 answer:
Vikki [24]3 years ago
3 0
2 :3 :4 gives 9 shares  (2 + 3 + 4)

9 shares = 120cm
1 share = 120/9 cm = 13 1/3 cm  ( or 13.333)

2 shares = 26 2/3 cm
3 shares = 40 cm
4 shares = 53 1/3 cm
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The cost to run Machine 1 for an hour is $2. During that
katen-ka-za [31]

Answer:

Math SMH

Step-by-step explanation:

8 0
2 years ago
Someone please help with this problem
den301095 [7]
A) write an equation you can solve to find the cost of one ticket
x=cost of one ticket.
9x+5=104

b)
I have to solve this equation.
1)adding -5 to each side
2) dividing both sides by 9

c)
9x+5=104
1) 9x+5-5=104-5
     9x=99
2) 9x/9=99/9
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the cost of each ticket was $11
 
3 0
3 years ago
What is the formula for volume of a square?
12345 [234]

Volume is measured of the objects which are three-dimensional .. And square is just a shape , hence it doesn't have any formula for volume .
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If you were tryna ask about cube , the formula for cube is s^3
Where s is the side of the cube

3 0
3 years ago
A linear regression model is fitted to the data x y 37.0 65.0 36.4 67.2 35.8 70.3 34.3 71.9 33.7 73.8 32.1 75.7 31.5 77.9 with x
andrey2020 [161]

Answer:

b0= 144.59

b= -2.12

Se²= 1.02

99%CI E(Y/X=35): [68.78; 71.99]

Step-by-step explanation:

Hello!

I've arranged the given data:

X: 37.0, 36.4, 35.8, 34.3, 33.7, 32.1, 31.5

Y: 65.0, 67.2, 70.3, 71.9, 73.8, 75.7, 77.9

The equation of the linear regression model is:

Yi= β₀ + βXi + εi

Where

Yi is the dependent variable

Xi is the independent variable

εi represents the errors or residues

β₀ is the intercept of the line

β is the slope

The conditions to make a linear regression analysis are:

For each given value of X, there is a population of Y~N(μy;σy²)

Each value of Y is independent of the others.

The population variances of each population of Y are equal.

From these conditions the following characteristic is deduced:

εi~N(0;σ²)

The parameters of the regression are:

β₀, β, and σ²

If the conditions are met then you can estimate the regression line:

Yi= bo * bXi + ei.

And the point estimation of the parameters can be calculated using the formulas:

β₀ ⇒ b0= (∑y/n)-b(∑x/n)

β ⇒ b= [∑xy- ((∑x)(∑y))/n]/(∑x²-((∑x)²/n))

σ²⇒ Se²= 1/(n-2)*[∑y²-(∑y)²/n - b²(∑x²-(∑x)²/n)]

n= 7

∑y= 501.80

∑y²= 36097.88

∑x= 240.80

∑x²= 8310.44

∑xy= 17204.87

b0= 144.59

b= -2.12

Se²= 1.02

The estimated regression line is:

Yi= 144.59 -2.12Xi

You need to calculate a 99%CI E(Y/X=35), the formula is:

(b0 + bX0) ± t_{n-2;1-\alpha /2}*\sqrt{S_e^2(\frac{1}{n}+\frac{(X_0-X[bar])^2}{sumX^2-(\frac{(sumX)^2}{n} )} )}

(144.59 + (-2.12*35)) ± 4.032*\sqrt{1.02(\frac{1}{7}+\frac{(35-34.4)^2}{8310.44-(\frac{(240.80)^2}{7} )} )}

[68.78; 71.99]

With a 99% confidence level youd expect that the interval [68.78; 71.99] contains the true value of the average of Y when X= 35.

I hope it helps!

6 0
3 years ago
In a survey of 3,300 people who owned a certain type of car, 660 said they would buy that type of car again. What percent of the
Stolb23 [73]

Answer:

20%

Step-by-step explanation:

660:3300*100 =

(660*100):3300 =

66000:3300 = 20

8 0
3 years ago
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