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2 years ago

_____, one of the greatest writers in history, emerged during the Renaissance.

SAT

2 answers:

Ivanshal [37]2 years ago

5 0

Hello ! :D

I am pretty sure, you already know the answer is?

But- I am still going to tell you. Cause- why not?

$\text{\underline{ANSWER :}}$

<h2><em>A. WILLIAN SHAKESPEARE.</em></h2><h2><em></em></h2>

<em></em> $\text{\underline{EXPLANATION :}}$ <em></em>

Because "William Shakespeare" was one of the greatest writers in the history during the time of the "Renaissance."

Hope It Helped!

<u>And Tell me if The answer is wrong. . .</u>

<u />

<h2><u>Good Luck With Your Assignment!</u></h2><h2><u></u></h2>

#LearnWithBrainly

$\text{\underline{ANSWER :}}$

$\textbf{Jace}$ ツ

$\boxed{\text{Carry on with Learning ! :D}}$

NeX [460]2 years ago

4 0

Answer:

Williaam shakespeare

Explanation:

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Find the residual values, and use the graphing calculator tool to make a residual plot.

finlep [7]

Answer:

No, the points are evenly distributed about the x-axis.

Explanation:

<u>1. Write the table with the data:</u>

x given predicted residual

1 - 3.5 - 1.1

2 - 2.9 2

3 - 1.1 5.1

4 2.2 8.2

5 3.4 1.3

<u>2. Complete the column of residuals</u>

The residual is the observed (given) value - the predicted value.

residual = given - predicted.

Thus, the complete table, with the residual values are:

x given predicted residual

1 - 3.5 - 1.1 - 2.4

2 - 2.9 2 - 4.9

3 - 1.1 5.1 - 6.2

4 2.2 8.2 - 6.0

5 3.4 1.3 2.1

<u>3. Residual plot</u>

You must plot the last column:

x residual

1 - 2.4

2 - 4.9

3 - 6.2

4 - 6.0

5 2.1

See the plot attached.

<em>Does the residual plot show that the line of best fit is appropriate for the data?</em>

Ideally, a residual plot for a line of best fit that is appropiate for the data must not show any pattern; the points should be randomly distributed about the x-axis.

But the points of the plot are not randomly distributed about the x-axis: there are 4 points below the x-axis and 1 point over the x-axis: there are more negative residuals than positive residuals. This is a pattern. Also, you could say that they show a curve pattern, which drives to the same conclusion: the residual plot shows that the line of best fit is not appropiate for the data.

Thus, the conclusion should be: No, the points have a pattern.

1. "<em>Yes, the points have no pattern</em>": false, because as shown, the points do have a pattern, which makes the residual plots does not show that the line of best fit is appropiate for the data.

2. "<em>No, the points are evenly distributed about the x-axis</em>": true. As already said the points have a pattern. It is a curved pattern, and this <em>shows the line of best fit is not appropiate for the data.</em>

3. "<em>No, the points are in a linear pattern</em>": false. The points are not in a linear pattern.

4. "<em>Yes, the points are in a curved pattern</em>": false. Because the points are in a curved pattern, the residual plot shows that the line of best fit is not appropiate for the data.