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3 years ago

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Mathematics

1 answer:

liraira [26]3 years ago

3 0

Answer:

what is the question dude

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The sum of the angle measures of a polygon with s sides is 2340. find s.

marta [7]

Answer:

s = 15.

Step-by-step explanation:

The formula for a polygon with s sides is:

Sum of the angles = 180(s - 2) so we have:

180(s - 2) = 2340

180s - 360 = 2340

180s = 2700

s = 15

8 0

3 years ago

To go to dance class at 6:45p.m. bus,Kelly needs 35 minutes to walk home from a friend's house,30 minutes for dinner,and 20 minu

GREYUIT [131]

20+35+30= 1 hr&25 min so she should leave at 5:20

5 0

3 years ago

An SRS of size 20 is drawn from a population that has a normal distribution. The sample has a mean of 122.5 and a standard devia

Tems11 [23]

Answer:

The value is $\sigma_{\= x} = 1.789$

Step-by-step explanation:

From the question we are told that

The sample size is n = 20

The sample mean is $\= x = 122.5$

The standard deviation is $s = 8$

Generally the standard error of the mean is mathematically represented as

$\sigma_{\= x} = \frac{s}{\sqrt{n} }$

=> $\sigma_{\= x} = \frac{8}{\sqrt{20 } }$

=> $\sigma_{\= x} = 1.789$

8 0

3 years ago

PLEASEEEE HELPPPPP!!!!!!!!

Feliz [49]

Answer:

C, thoughtful and grntle

5 0

3 years ago

Read 2 more answers

. The estimate regression equation for a model involving two independent variables and 10 observations follows.y = 29.1270 + 0.5

beks73 [17]

Answer:

b) y = 289.815 when $x_1 = 180 \text{ and } x_2 = 310$

Step-by-step explanation:

We are given the following information in the question:

$y = 29.1270 + 0.5906x_1 + 0.4980x_2$

where y is the dependent variable,

$x_1, x_2$ are the independent variable.

The multiple regression equation is of the form:

$y = b_0 + b_1x_1 + b_2x_2$

where,

$b_0$ : is the intercept of the equation and is the value of dependent variable when all the independent variable are zero.

$b_1$ : It is the slope coefficient of the independent variable $x_1$ .

$b_2$ : It is the slope coefficient of the independent variable $x_2$ .

The regression coefficient in multiple regression is the slope of the linear relationship between the dependent and the part of a predictor variable that is independent of all other predictor variables.

Comparing the equations, we get:

$b_1 = 0.5906\\b_2 = 0.4980$

This means holding $x_2$ constant, a change of one in $x_1$ is associated with a change of 0.5906 in the dependent variable.

This means holding $x_1$ constant, a change of 1 in $x_2$ is associated with a change of 0.4980 in the dependent variable.

b) We have to estimate the value of y

$y = 29.1270 + 0.5906(180) + 0.4980(310) = 289.815$

3 0

3 years ago