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monitta
3 years ago
14

Which translation vectors could have been used for the pair of figures?

Mathematics
2 answers:
Ierofanga [76]3 years ago
7 0

if set up like

1 2

3 4

5 6

it would be 4 and 6

julia-pushkina [17]3 years ago
5 0

Answer:

The translation vectors are shown in below figure.

Step-by-step explanation:

In a translation of figures, if translation is described using vectors, then the vector that represents the distance and direction between preimage and image, is known as  translation vectors.

In the given figure image and preimage are not mentioned and we need to find the translation vectors.

Case 1: Let (1) is preimage and (2) is image.

Connect any two corresponding vertices of preimage and image by using vectors.

Case 2: Let (2) is preimage and (1) is image.

Connect any two corresponding vertices of preimage and image by using vectors.

Therefore the translation vectors are shown in below figure.

If the oppositions are in the following way,

1       2

3       4

5       6

Then the correct options are 4 and 6.

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Step-by-step explanation:

n = sample size = 5

a) Let us determine the sum

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

\sum x_i^2= 100^2+200^2+300^2+400^2+490^2=540100

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\sum y_i^2= 237^2+350^2+419^2+465^2+507^2=827504

\sum x_i y_i=100  \times 237 + 200\times350+300 \times 419 + 400 \times 465 +  490 \times 507=653830

Now we can determine S_x_x, S_x_y, S_y_y

S_x_x = \sum x_i^2-\frac{(\sum x_1)^2}{n} \\= 540100 - \frac{1490^2}{5} \\= 96080

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

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b)

<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
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