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Answer:
It should be noted that the Great Compromise combined elements of Virginia and New Jersey plan.
According to this question, we are to discuss the regions that serves as the combined elements of Great Compromise.
As a result of this we can see that the two regions which serves as two plans element that influence Great Compromise is Virginia and New Jersey and this comprise was signed into effect in 1787.
Therefore, Great Compromise combined elements of Virginia and New Jersey plan.
Learn more about The Great Compromise at:
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Explanation:
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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.
Explanation:
A longitudinal wave is composed of compressions and rarefactions. An example of a lomgitudinal wave is sound waves. It's a type of wave thay moves parrelel to axis.
Answer:
Yes
Explanation:
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