Answer:
The first choice is correct
Answer: -512
Step-by-step explanation:
(18-26) = -8
(-8)^3 = (-8)*(-8)*(-8) = -512
Answer:
B) -3 (Sorry if its overwhelming)
Explanation:
First, we have the given information of the weather over a <em>2</em> and <em>1/5</em> <em>span</em>
And we are asked to find the change per hour
We can first start by finding the <em>change</em> for 2 and 1/5 hours:
- Subtract the first amount by the second amount.
= (-6 3/5) - 0
= (-6 3/5) + 0
= -6 3/5
Now that we have the change for <em>2 and 1/5 hours</em> we must find the <em>change</em> per hour:
- Divide the given dividend by the given divisor
= -6 3/5 ÷ 2 1/5
= -3
Hence, the temperature <em>change per hour</em> over a 2 1/5 hour span is -3° per hour
Answer:
Step-by-step explanation:
I dont have cashapp sorry
Answer:
Types of Relationships between the Input and Output
The scatter plot can be a useful tool in understanding the type of relationship that exist between the inputs (X’s) and the outputs (Y’s)
Step-by-step explanation:
1. No Relationship: The scatter plot can give an obvious suggestion if the inputs and outputs on the graph are not related. The points will be scattered throughout the graph with no particular pattern. For no relationship to exist, points have to be completely diffused. If some points are in concentration, then maybe a relationship does exist and our analysis has not been able to uncover it.
2. Linear and Non-Linear: A linear correlation exists when all the points are plotted close together. They form a distinct line. On the other hand points could be close together but they could form a relationship which has curves in it. The nature of the relationship has wide ranging implications.
3. Positive and Negative: A positive relationship between the inputs and the outputs is one wherein more of one input leads to more of an output. This is also known as a direct relationship.
On the other hand a negative relationship is one where more of one input leads to less of another output. This is also known as an inverse relationship.
4. Strong and Weak: The strength of the correlation is tested by how closely the data fits the shape. For instance if all the points are scattered very close together to form a very visible line then the relationship is strongly linear. On the other hand, if the relationship does not so obviously fit the shape then the relationship is weak.
I don't know if this was exactly what you were looking for; hope it is! :)
