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Nastasia [14]
3 years ago
5

An instructor measured quiz scores and the number of hours studying among a sample of 20 college students. If SSXY = 43, SSX = 9

8, MY = 6, and MX = 4, then what is the regression equation for this sample? (Round your numerical values to three decimal places.) Y hat = X +
Mathematics
1 answer:
UNO [17]3 years ago
5 0

Answer:

The regression equation for the sample is

Y= 0.430x +0.214

Step-by-step explanation:

Using the regression formula;

a= (nSSXY - MX MY)/(nSSX -MX^2)

a= (20×43- 4×6)/(20×98 - (4^2))

a= 836/(1960-16)

a= 836/1944

a= 0.430

X bar= summation x / n =4/20= 0.2

Y bar= summation y / n =6/20 = 0.3

b= y bar - a xbar

b= 0.3 - 0.430(0.2)

b= 0.3- 0.086

b= 0.214

The regression equation

Y= ax + b

Y= 0.430x +0.214

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Answer:

See solution below

Step-by-step explanation:

According to pythagoras theorem

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b^2 = 100-16

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b = √84

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Using SOH CHA TOA identity

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Use Euler's method with step size 0.2 to estimate y(1), where y(x) is the solution of the initial-value problem y' = x2y − 1 2 y
irina [24]

Answer:

Therefore the value of y(1)= 0.9152.

Step-by-step explanation:

According to the Euler's method

y(x+h)≈ y(x) + hy'(x) ....(1)

Given that y(0) =3 and step size (h) = 0.2.

y'(x)= x^2y(x)-\frac12y^2(x)

Putting the value of y'(x) in equation (1)

y(x+h)\approx y(x) +h(x^2y(x)-\frac12y^2(x))

Substituting x =0 and h= 0.2

y(0+0.2)\approx y(0)+0.2[0\times y(0)-\frac12 (y(0))^2]

\Rightarrow y(0.2)\approx 3+0.2[-\frac12 \times3]    [∵ y(0) =3 ]

\Rightarrow y(0.2)\approx 2.7

Substituting x =0.2 and h= 0.2

y(0.2+0.2)\approx y(0.2)+0.2[(0.2)^2\times y(0.2)-\frac12 (y(0.2))^2]

\Rightarrow y(0.4)\approx  2.7+0.2[(0.2)^2\times 2.7- \frac12(2.7)^2]

\Rightarrow y(0.4)\approx 1.9926

Substituting x =0.4 and h= 0.2

y(0.4+0.2)\approx y(0.4)+0.2[(0.4)^2\times y(0.4)-\frac12 (y(0.4))^2]

\Rightarrow y(0.6)\approx  1.9926+0.2[(0.4)^2\times 1.9926- \frac12(1.9926)^2]

\Rightarrow y(0.6)\approx 1.6593

Substituting x =0.6 and h= 0.2

y(0.6+0.2)\approx y(0.6)+0.2[(0.6)^2\times y(0.6)-\frac12 (y(0.6))^2]

\Rightarrow y(0.8)\approx  1.6593+0.2[(0.6)^2\times 1.6593- \frac12(1.6593)^2]

\Rightarrow y(0.6)\approx 0.8800

Substituting x =0.8 and h= 0.2

y(0.8+0.2)\approx y(0.8)+0.2[(0.8)^2\times y(0.8)-\frac12 (y(0.8))^2]

\Rightarrow y(1.0)\approx  0.8800+0.2[(0.8)^2\times 0.8800- \frac12(0.8800)^2]

\Rightarrow y(1.0)\approx 0.9152

Therefore the value of y(1)= 0.9152.

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