What is the answer to the question " 6(5x(41-36)-(8+14))

WILL GIVE BRAINLIEST PLZZZZ HELP

bija089 [108]

Answer: y= 8295

Step-by-step explanation:

3 0

3 years ago

Find the mean absolute deviation of the following set of data.

Katen [24]

Answer:

The mean absolute deviation is 5.952 ⇒ 3rd answer

Step-by-step explanation:

* Lets talk about the mean absolute deviation

- Mean absolute deviation (MAD) of a data set is the average distance

between each data value and the mean

1- To find the mean absolute deviation of the data, start by finding

the mean of the data set.

2- Find the sum of the data values, and divide the sum by the

number of data values.

3- Find the absolute value of the difference between each data value

and the mean ⇒ |data value – mean|

4- Find the sum of the absolute values of the differences.

5- Divide the sum of the absolute values of the differences by the

number of data values

* Now lets solve the problem

- The set of data is 31.8 , 22.6 , 13.8 , 16.4 , 28.1

# Find the mean

∵ The mean = sum/ number

∴ The mean = (31.8 + 22.6 + 13.8 + 16.4 + 28.1)/5 = 112.7/5 = 22.54

# Find |data value – mean|

∵ I31.8 - 22.54I = 9.26

∵ I22.6 - 22.54I = 0.06

∵ I13.8 - 22.54I = 8.74

∵ I16.4 - 22.54I = 6.14

∵ I28.1 - 22.54I = 5.56

# Find the sum of the absolute values

∴ The sum = 9.26 + 0.06 + 8.74 + 6.14 + 5.56 = 29.76

# Find the mean absolute deviation

∵ The mean absolute deviation = sum of absolute values/number

∴ The mean absolute deviation = 29.76/5 = 5.952

* The mean absolute deviation is 5.952

5 0

4 years ago

What’s the answer and work? Someone please tell me

SCORPION-xisa [38]

Answer:

the forth top price is $93

Step-by-step explanation:

(30 + 15 + 18 + x)/4 = 39

63 + x/4 = 39

63 + x = 39 × 4

63 + x= 156

63 + x - 63 = 156 - 63

x = 93

brainliest is appreciated

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

(c) y = -12.629 + 0.0654x

(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

I have a rectangle with a length of 7 cm and a perimeter of 38 cm. Find the area of the rectangle?

const2013 [10]

Answer:

first find the width

=11cm

find area

7×11=77

and=77

3 0

3 years ago