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sergeinik [125]
3 years ago
13

Find the measure of each numbered angle in the rectangle

Mathematics
1 answer:
azamat3 years ago
6 0

m∠1=31

m∠2=59

m∠3=90

m∠4=31

m∠5=90

hope this helps brainliest please!

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After 273 m3 of ethylene oxide is formed at 748 kPa and 525 K, the gas is cooled at constant volume to 293 K.The new pressure is
Anuta_ua [19.1K]
P1/T1 = P2/T2 

<span>748 / 525 = P2/293 </span>

<span>P2 = 748/525 X 293 = 417.455 kPa </span>
5 0
3 years ago
Read 2 more answers
Hellppppp pleaseeeee
Eduardwww [97]

Answer:

The answer would be C,

Yes the graph passes the vertical line test

6 0
3 years ago
Carlos received 84 votes. That was 3 of every 7 votes cast in the class president election. How many votes were cast?
Step2247 [10]
336 votes total.

if he got 84 votes 3/7 so you take 84 times 4 (i got four by subracting 3 from 7 and got the remaining votes) and you will get 336 votes. hope this helps! :)
5 0
3 years ago
Convert 0.0425 as a fraction in its simplest form​
Sholpan [36]

Answer:

17/400

Step-by-step explanation:

.0425 = 425/10,000

this can be simplified to be 17/400

8 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
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