Mathematics
06.08.2021 04:52
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PLEASE HELP I WILL GIVE BRAINLIEST Which statement accurately describes the scatterplot

PLEASE HELP I WILL GIVE BRAINLIEST

Which statement accurately describes the scatterplot
PLEASE HELP I WILL GIVE BRAINLIEST 
Which statement accurately describes the scatterplot
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mairadua14
mairadua14
4,7(80 marks)

B is the answer for sure, because there are two outliers, there is a visible line, and they are not at all clustered around a single point

zakariahassan3482
zakariahassan3482
4,8(69 marks)

Now you can give the other guy brainliest.

Step-by-step explanation:

jvontaemyles14
jvontaemyles14
4,7(7 marks)

y=0.259 x +10.447

Now we can find the residulls like this:

e_1 = 17.3 - 17.375 = -0.075

e_2 = 17.1 - 17.052 = 0.049

e_3 = 17.3 - 17.311 = -0.011

e_4 = 17.5 - 17.440 = 0.06

e_5 = 16.9 - 16.922 = -0.022

So then we can see that the residuals are not with an specified pattern (alternating sign) so then we can conclude that are distributed normally

Step-by-step explanation:

We have the following data given:

Height (inches), x 26.75 25.5 26.5 27 25

Head Circumference (inches), y 17.3 17.1 17.3 17.5 16.9

We need to find a linear model y = mx +b

For this case we need to calculate the slope with the following formula:

m=\frac{S_{xy}}{S_{xx}}

Where:

S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i)}{n}

S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}

So we can find the sums like this:

\sum_{i=1}^n x_i =130.75

\sum_{i=1}^n y_i =86.1

\sum_{i=1}^n x^2_i =3422.06

\sum_{i=1}^n y^2_i = 1482.85

\sum_{i=1}^n x_i y_i =2252.28

With these we can find the sums:

S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}=3422.06-\frac{130.75^2}{5}=2.95

S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i)}=2252.28-\frac{130.75*86.1}{5}=0.765

And the slope would be:

m=\frac{0.765}{2.95}=0.259

Nowe we can find the means for x and y like this:

\bar x= \frac{\sum x_i}{n}=\frac{130.75}{5}=26.15

\bar y= \frac{\sum y_i}{n}=\frac{86.1}{5}=17.22

And we can find the intercept using this:

b=\bar y -m \bar x=17.22-(0.259*26.15)=10.447

So the line would be given by:

y=0.259 x +10.447

Now we can find the residulls like this:

e_1 = 17.3 - 17.375 = -0.075

e_2 = 17.1 - 17.052 = 0.049

e_3 = 17.3 - 17.311 = -0.011

e_4 = 17.5 - 17.440 = 0.06

e_5 = 16.9 - 16.922 = -0.022

So then we can see that the residuals are not with an specified pattern (alternating sign) so then we can conclude that are distributed normally

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