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2 years ago

Please help me with this problem.

Mathematics

1 answer:

son4ous [18]2 years ago

7 0

Answer:

y = 10/2x + 0

Step-by-step explanation:

Slope Int Form: y = m(slope)x + b(y-intercept)

The number before the x is the slope. To find the slope, count how far up or down and how far to the right or left. The b in the equation is the y-int so find the y-int of the graph.

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Add or subtract, represent each equation with a number line subtract -28 - (-16)=

Kitty [74]

-28 - (-16)

-28 + 16 two negatives equals a positive.

-12 <<< your answer

hope this helps, God bless!

7 0

3 years ago

What is the slope of the line represented by the equation y =4/5x-3?

Leno4ka [110]

Answer:

4/5 is the slope of the line

7 0

2 years ago

Can someone help me please?

svlad2 [7]

Answer:

∠2 and ∠5 are corresponding angles

Step-by-step explanation:

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3 years ago

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Archy [21]

Answer:

A and C

<em>I hope this helps! ^^</em>

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2 years ago

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A sample of 5 strings of thread is randomly selected and the following thicknesses are measured in millimeters. Give a point est

liq [111]

Answer:

$s^2 = \frac{(1.48-1.502)^2 +(1.45-1.502)^2 +(1.54-1.502)^2 +(1.52-1.502)^2 +(1.52-1.502)^2}{5-1} =0.00132$

And for the deviation we have:

$s= \sqrt{0.00132}=0.0363$

And that value represent the best estimator for the population deviation since:

$E(s) =\sigma$

Step-by-step explanation:

For this case we have the following data:

1.48,1.45,1.54,1.52,1.52

The first step for this cae is find the sample mean with the following formula:

$\bar X =\frac{\sum_{i=1}^n X_}{n}$

And replacing we got:

$\bar X= \frac{1.48+1.45+1.54+1.52+1.52}{5} = 1.502$

And now we can calculate the sample variance with the following formula:

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

And replacing we got:

$s^2 = \frac{(1.48-1.502)^2 +(1.45-1.502)^2 +(1.54-1.502)^2 +(1.52-1.502)^2 +(1.52-1.502)^2}{5-1} =0.00132$

And for the deviation we have:

$s= \sqrt{0.00132}=0.0363$

And that value represent the best estimator for the population deviation since:

$E(s) =\sigma$

4 0

3 years ago

Read 2 more answers