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TiliK225 [7]
3 years ago
9

A Cepheid variable star is a star whose brightness alternately increases and decreases. For a certain star, the interval between

times of maximum brightness is 3.8 days. The average brightness of this star is 2.0 and its brightness changes by ±0.35. In view of these data, the brightness of the star at time t, where t is measured in days, has been modeled by the function
Mathematics
1 answer:
fomenos3 years ago
5 0

Answer:

0.41 (correct to 2 decimal place)

Step-by-step explanation:

If B(t)=4.0+0.35sin\frac{2\pi t }{5.4}

Let u=\frac{2\pi t }{5.4}, then B(u)=4.0+0.35sin u

We want to determine the rate of increase \frac{dB}{dt} after one day

du=\frac{2\pi dt }{5.4} and \frac{dB}{du}  =0.35cos u

\frac{dB}{dt}=\frac{2\pi }{5.4}0.35cos (\frac{2\pi t }{5.4})=0.407cos (\frac{2\pi t }{5.4})

B^{'} (t)=0.407cos (\frac{2\pi t }{5.4})

Rate of increase after one day, i.e. t=1

B^{'} (1)=0.407cos (\frac{2\pi X 1 }{5.4})= 0.407 =0.41 (correct to 2 decimal place)

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The difference between the observed value of the dependent variable and the value predicted using the estimated regression equat
Elenna [48]

Answer:

For this case we define the dependent variable as Y and the independent variable X. We assume that we have n observations and that means the following pairs:

(x_1, y_1) ,....,(x_n,y_n)

For this case we assume that we want to find a linear regression model given by:

\hat y = \hat m x +\hat b

Where:

\hat m represent the estimated slope for the model

\hat b represent the estimated intercept for the model

And for any estimation of the dependent variable \hat y_i , i=1,...,n is given by this model.

The difference between the observed value of the dependnet variable and the value predicted using the estimated regression equation is known as residual, and the residual is given by this formula:

e_i = y_i -\hat y_i , i=1,...,n

So the best option for this case is:

d. residual

Step-by-step explanation:

For this case we define the dependent variable as Y and the independent variable X. We assume that we have n observations and that means the following pairs:

(x_1, y_1) ,....,(x_n,y_n)

For this case we assume that we want to find a linear regression model given by:

\hat y = \hat m x +\hat b

Where:

\hat m represent the estimated slope for the model

\hat b represent the estimated intercept for the model

And for any estimation of the dependent variable \hat y_i , i=1,...,n is given by this model.

The difference between the observed value of the dependnet variable and the value predicted using the estimated regression equation is known as residual, and the residual is given by this formula:

e_i = y_i -\hat y_i , i=1,...,n

So the best option for this case is:

d. residual

7 0
3 years ago
Trigonometry questions
trasher [3.6K]

We'll use standard labeling of right triangle ABC, C=90 degrees, legs a, b, hypotenuse c.

11.

Right triangle, cliff peak A, boat B, angle opposite cliff is B=28.9 deg. adjacent leg a=65.7 m, cliff height is leg b.

tan B = b/a

b = a tan B = 65.7 tan 28.9° = 36.3 m

12.

Similar story, boat at B, opposite b=3.5 m, rope c=12 m

sin B = b/c

B = arcsin b/c = arcsin (3.5/12) = 17.0°

13.

c=124 m, A=58°

sin A = a/c

a = c sin A = 124 sin 58 = 105.2 m

14.

That's a hypotenuse c=4-1.2 = 2.8 m to a height b=1.8m so

cos A = b/c

A = arccos b/c = arccos (1.8/2.8) = 50.0°

15.

Not a right triangle, an isosceles triangle.  Half of it is a right triangle with hypotenuse one arm, c=9.8 cm and angle opposite half the base of B=62/2=31°.  We're after d=2b:

sin B = b/c

b = c sin B

d = 2b = 2 c sin B = 2(9.8) sin 31 = 10.1 cm

Almost equilateral


4 0
3 years ago
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