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3 years ago

In what way can a political party be classified as a linkage institution?

Mathematics

1 answer:

Natali5045456 [20]3 years ago

7 0

Answer:

A political party is a linkage institution that is characterized by a group of people joined together by common philosophies.

Step-by-step explanation:

The main goal of a political party is to nominate individuals to get elected to local, state, and national offices in order to develop and implement public policy.

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Find the midpoint of the segment with the following endpoints. (10,6) and (6, 10)

lys-0071 [83]

Midpoint = ( x1 + x2)/2, (y1+ y2)/2

Midpoint = (10 +6)/2, (6+10)/2

Midpoint = (8,8)

3 0

3 years ago

Please answer if you know the answer! [Help]

Alinara [238K]

Remember that an exponent means repeated multiplication.

The exponent of 4 means you have four $\big(b^2\big)$ 's mutiplied together:

$\big(b^2\big)\cdot\big(b^2\big)\cdot\big(b^2\big)\cdot\big(b^2\big)$

And then each exponent of 2 inside means you have two $b$ 's multiplied inside each set of parentheses.:

$\big(b\cdot b\big)\cdot\big(b\cdot b\big)\cdot\big(b\cdot b\big)\cdot\big(b\cdot b\big)$

There are 8 b's there when you expand this out.

6 0

3 years ago

Sophia used the Order of Operations to simplify 4(5 - 2) to 4x3.

Alchen [17]

Answer:

Step-by-step explanation:

Order of operations, use the operation within the parenthesis:

1) 5 - 2 = 3
2) 4*3 = 12

Distributive property, a(b + c) = ab + ac:

1) 4*5 - 4*2 = 20 - 8
2) 20 - 8 = 12

Both ways are correct and lead to same result

5 0

3 years ago

Help please Question is in the picture

anzhelika [568]

Answer:

360 degrees in total.

Step-by-step explanation:

We are given that the m∠1 is 145 degrees, and because ∠1 and ∠2 form a straight line we can tell that 180-145 = 35.

So now here's what we know:

m∠1 = 145

m∠2 = 35

After that, we need to look at ∠5 and ∠6.

One thing we can notice right away is that ∠5 and ∠6 should measure the same as ∠1 and ∠2 (respectively) because they are corresponding angles.

Now we will add them all together to find the sum of all four angles.

m∠1 = 145 + m∠2 = 35 = 180

m∠5= 145 + m∠6 = 35 = 180

180 + 180 = 360

8 0

3 years ago

The time it takes for a planet to complete its orbit around a particular star is called the? planet's sidereal year. The siderea

BartSMP [9]

Answer:

(a) See below

(b) r = 0.9879

(d) See below

(e) No.

Step-by-step explanation:

(a) Plot the data

I used Excel to plot your data and got the graph in Fig 1 below.

(b) Correlation coefficient

One formula for the correlation coefficient is

$r = \dfrac{\sum{xy} - \sum{x} \sum{y}}{\sqrt{\left [n\sum{x}^{2}-\left (\sum{x}\right )^{2}\right]\left [n\sum{y}^{2} -\left (\sum{y}\right )^{2}\right]}}$

The calculation is not difficult, but it is tedious.

(i) Calculate the intermediate numbers

We can display them in a table.

x y xy x² y²

36 0.22 7.92 1296 0.05

67 0.62 42.21 4489 0.40

93 1.00 93.00 20164 3.46

433 11.8 5699.4 233289 139.24

887 29.3 25989.1 786769 858.49

1785 82.0 146370 3186225 6724

2797 163.0 455911 7823209 26569

3675 248.0 911400 13505625 61504

9965 537.81 1545776.75 25569715 95799.63

(ii) Calculate the correlation coefficient

$r = \dfrac{\sum{xy} - \sum{x} \sum{y}}{\sqrt{\left [n\sum{x}^{2}-\left (\sum{x}\right )^{2}\right]\left [n\sum{y}^{2} -\left (\sum{y}\right )^{2}\right]}}\\\\= \dfrac{9\times 1545776.75 - 9965\times 537.81}{\sqrt{[9\times 25569715 -9965^{2}][9\times 95799.63 - 537.81^{2}]}} \approx \mathbf{0.9879}$

(c) Regression line

The equation for the regression line is

y = a + bx where

$a = \dfrac{\sum y \sum x^{2} - \sum x \sum xy}{n\sum x^{2}- \left (\sum x\right )^{2}}\\\\= \dfrac{537.81\times 25569715 - 9965 \times 1545776.75}{9\times 25569715 - 9965^{2}} \approx \mathbf{-12.629}\\\\b = \dfrac{n \sum xy - \sum x \sum y}{n\sum x^{2}- \left (\sum x\right )^{2}} - \dfrac{9\times 1545776.75 - 9965 \times 537.81}{9\times 25569715 - 9965^{2}} \approx\mathbf{0.0654}\\\\\\\text{The equation for the regression line is $\large \boxed{\mathbf{y = -12.629 + 0.0654x}}$}$

(d) Residuals

Insert the values of x into the regression equation to get the estimated values of y.

Then take the difference between the actual and estimated values to get the residuals.

x y Estimated Residual

36 0.22 -10 10

67 0.62 -8 9

93 1.00 -7 8

142 1.86 -3 5

433 11.8 19 - 7

887 29.3 45 -16

1785 82.0 104 -22

2797 163.0 170 - 7

3675 248.0 228 20

(e) Suitability of regression line

A linear model would have the residuals scattered randomly above and below a horizontal line.

Instead, they appear to lie along a parabola (Fig. 2).

This suggests that linear regression is not a good model for the data.

4 0

3 years ago