Considering that the data has no outliers, the mean of 3.2 inches should be used to describe the center of the data represented in this line plot.
<h3>What measure should be used to describe the center of a data-set?</h3>
It depends if the data-set has outliers or not.
- If it does not have outliers, the mean should be used.
- If it has, the median should be used.
The dot plot gives the number of times each measure appears. Since there is no outliers, that is, all values are close, the mean should be used. It is given by:
M = (2 x 1 + 3 x 2 + 2 x 3 + 1 x 5 + 1 x 6 + 1 x 7)/(2 + 3 + 2 + 1 + 1 + 1) = 3.2 inches.
The mean of 3.2 inches should be used to describe the center of the data represented in this line plot.
More can be learned about the mean of a data-set at brainly.com/question/24628525
Answer:
4(x-2)(x+3)
- Factor a GCF from the expression, if possible.
- Factor a Trinomial, if possible.
- Factor a Difference Between Two Squares as many times as possible.
Please Mark Brainliest If This Helped!
F(-11/5)=5(-11/5)+6
f(-11/5) = -11+6
<span>f(-11/5) = -5
Hope this helps!</span>
Answer:
It is B
Step-by-step explanation:
(c² - 6c) + (7c + 5)
c² is it's own term
-6c + 7c combine to 'c'
5 is it's own term.
So it is c² + c +5
Answer: Choice C
Amy is correct because a nonlinear association could increase along the whole data set, while being steeper in some parts than others. The scatterplot could be linear or nonlinear.
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Explanation:
Just because the data points trend upward (as you go from left to right), it does not mean the data is linearly associated.
Consider a parabola that goes uphill, or an exponential curve that does the same. Both are nonlinear. If we have points close to or on these nonlinear curves, then we consider the scatterplot to have nonlinear association.
Also, you could have points randomly scattered about that don't fit either of those two functions, or any elementary math function your teacher has discussed so far, and yet the points could trend upward. If the points are not close to the same straight line, then we don't have linear association.
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In short, if the points all fall on the same line or close to it, then we have linear association. Otherwise, we have nonlinear association of some kind.
Joseph's claim that an increasing trend is not enough evidence to conclude the scatterplot is linear or not.
