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3 years ago

8

Durante un partido de futbol un delantero hizo 45 lanzamientos en la porteria y de esos anoto 27 goles, cual fue el porcentaje d

e aciertos del jugador

1 answer:

Sonja [21]3 years ago

8 0

<span>Which of the following can cause a country to NOT fit the Demographic Transition Model?</span>

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Write the number 0.0049 in scientific notation.

jeka57 [31]

Answer:

4.9000

if it is correct answer then please follow me

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3 years ago

Anybody know the answers? A-? B-4 c-12 1/3?

shutvik [7]

Answer:

11.666666-repeated on and on

Step-by-step explanation:

but you can probably round to 11.7

7 0

3 years ago

If you were to solve the equation x+14=22, what steps would you take to solve this equation?

inessss [21]

subtract 14 from 22 to isolate the variable

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2 years ago

In a study relating the degree of warping, in mm, of a copper plate (y) to temperature in °C (x), the following summary statisti

kipiarov [429]

Answer:

The error sum of squares is SSE=12.97

The regression sum of squares is SSR=6.430

The total sum of squares is SST=19.4

Step-by-step explanation:

Linear regression is a way "to modeling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables)".

Regression estimates are "used to describe data and to explain the relationship between one dependent variable and one or more independent variables"

The linear model is given by the following equation $Y=mx +b$ , where y is the dependent variable, x the independent variable, m the slope and b the intercept.

For this case we have the following info given:

$\sum_{i=1}^n (x_i -\bar x)^2 =98775$

$\sum_{i=1}^n (y_i -\bar y)^2 =19.4$

$\bar x =26.36$

$\bar y =0.5188$

n= 40 represent the sample size

$\sum_{i=1}^n (x_i -\bar x)(y_i -\bar y) =796.94$

The total sum of squares is given by this formula:

$SST= \sum_{i=1}^n (y_i -\bar y)^2 =19.4$

And from the formulas for a simple regression, we need to calculate the slope for the regression like this:

$m=\frac{\sum_{i=1}^n (x_i -\bar x)(y_i -\bar y)}{\sum_{i=1}^n (x_i -\bar x)^2}$

And if we replace the values given we have:

$m=\frac{796.94}{98775}=0.008068$

We have another useful equation in order to find the sum of squares for the regression, given by:

$SSR=m* \sum_{i=1}^n (x_i -\bar x)(y_i -\bar y)=0.008068*796.94=6.430$

And we know this equivalence:

$SST= SSR+SSE$

And solving for the sum of squares for the error we have:

$SSE=SST-SSR=19.4-6.430=12.97$

So then we have the final solutions:

The error sum of squares is SSE=12.97

The regression sum of squares is SSR=6.430

The total sum of squares is SST=19.4

6 0

3 years ago

Help..................

elena-14-01-66 [18.8K]

Triangle has 180 degrees:
180=2m-3+m+4+3m+5
Combine like terms
180 = 6m+6
Subtract 6 from 180
174=6m
Divide by 6
m=29

Brainliest if that helped, please :)

5 0

2 years ago

Read 2 more answers