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algol13
4 years ago
11

Write the equation of the best fit line in slope-intercept form. Include all of your calculations in your final answer.

Mathematics
1 answer:
Dovator [93]4 years ago
3 0
I am not good at this so ii wont be able to solve it for ya but i can help you.

So to find the line of best fit you have to pick to pick to points on your scatter plot. Then with those two points you add the y points together then add the x points together. Your equation with be what you got in all y over x. That is your slope. I hope this helped you!
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What is the y-coordinate of the point that divides the
natima [27]

Answer:

y-coordinate = 0

Step-by-step explanation:

Consider the below diagram attached with this question.

Section formula:

If a point divides a line segment in m:n whose end points are (x_1,y_1) and (x_2,y_2), then the coordinates of that point are

(\frac{mx_2+nx_1}{m+n},\frac{my_2+ny_1}{m+n})

From the below graph it is clear that the coordinates of end points are J(1,-10) and K(7,2). A point divides the line JK is 5:1.

Using section formula, the coordinates of that point are

(\frac{(5)(7)+(1)(1)}{5+1},\frac{(5)(2)+(1)(-10)}{5+1})

(\frac{35+1}{6},\frac{10-10}{6})

(\frac{36}{6},\frac{0}{6})

(6,0)

Therefore, the y-coordinate of the point that divides the directed line segment from J to k into a ratio of 5:1 is 0.

8 0
3 years ago
Read 2 more answers
A sample of blood pressure measurements is taken for a group of​ adults, and those values​ (mm Hg) are listed below. The values
Slav-nsk [51]

Answer:

Systolic on right

\hat{CV} =\frac{18.68}{127.5}=0.147

Systolic on left

\hat{CV} =\frac{12.65}{74.2}=0.170

So for this case we have more variation for the data of systolic on left compared to the data systolic on right but the difference is not big since 0.170-0.147 = 0.023.

Step-by-step explanation:

Assuming the following data:

Systolic (#'s on right) Diastolic (#'s on left)

117; 80

126; 77

158; 76

96; 51

157; 90

122; 89

116; 60

134; 64

127; 72

122; 83

The coefficient of variation is defined as " a statistical measure of the dispersion of data points in a data series around the mean" and is defined as:

CV= \frac{\sigma}{\mu}

And the best estimator is \hat {CV} =\frac{s}{\bar x}

Systolic on right

We can calculate the mean and deviation with the following formulas:

[te]\bar x = \frac{\sum_{i=1}^n X_i}{n}[/tex]

s= \frac{\sum_{i=1}^n (x_i -\bar X)^2}{n-1}

For this case we have the following values:

\bar x = 127.5, s= 18.68

So then the coeffcient of variation is given by:

\hat{CV} =\frac{18.68}{127.5}=0.147

Systolic on left

For this case we have the following values:

\bar x = 74.2 s= 12.65

So then the coeffcient of variation is given by:

\hat{CV} =\frac{12.65}{74.2}=0.170

So for this case we have more variation for the data of systolic on left compared to the data systolic on right but the difference is not big since 0.170-0.147 = 0.023.

4 0
3 years ago
IM ASKING A QUESTION PLZ DON'T REPORT ME
victus00 [196]

Answer:im bored

Step-by-step explanation:

6 0
3 years ago
Read 2 more answers
How to subtract hexadecimal number when one is bigger than the other?
Inessa05 [86]
Hello,

In order to be simple: let's code hexadecimal numbers on 4 digits.

Example: 500-200=300 (in décimal)

500_{10}=01F4_{16}\\\\
200_{10}=00C8_{16}\\\\
For\ subtract\ 00C8\ we\ calculate\ 15th\ complement\\\\
C_{15}(00C8)=FF37\\\\

16th\ complement= FF37+0001=FF38\\\\

Then\ we\ add\\\\

01F4+FF38=(1)012C\ on\4\ digits:\ 012C\\

012C_{16}=300_{16}


7 0
3 years ago
Triangle Proofs Please help
oksian1 [2.3K]

Explanation:

There may be a more direct way to do this, but here's one way. We make no claim that the statements used here are on your menu of statements.

<u>Statement</u> . . . . <u>Reason</u>

2. ∆ADB, ∆ACB are isosceles . . . . definition of isosceles triangle

3. AD ≅ BD

and ∠CAE ≅ ∠CBE . . . . definition of isosceles triangle

4. ∠CAE = ∠CAD +∠DAE

and ∠CBE = ∠CBD +∠DBE . . . . angle addition postulate

5. ∠CAD +∠DAE ≅ ∠CBD +∠DBE . . . . substitution property of equality

6. ∠CAD +∠DAE ≅ ∠CBD +∠DAE . . . . substitution property of equality

7. ∠CAD ≅ ∠CBD . . . . subtraction property of equality

8. ∆CAD ≅ ∆CBD . . . . SAS congruence postulate

9. ∠ACD ≅ ∠BCD . . . . CPCTC

10. DC bisects ∠ACB . . . . definition of angle bisector

4 0
2 years ago
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