In order to answer this question, we must break this mathematical expression up into a series of mathematical operations (exponent, multiplication,division, addition, and/or subtraction):
"4 times a number" - The word "times" implies that we have to multiply 4 by an unknown number. We can simply label this unknown number as x.
"cubed" - In order to "cube" a number, we must raise it to the third power, or have an exponent of 3. Our unknown number of x now becomes x3 because we raised it to the third power.
"decreased by 7" - The word "decreased" implies that we must subtract 7 from the product of 4 multiplied by x3
With all of the information we now have, we can form an algebraic expression for this problem.
"4 times a number cubed decreased by 3" now becomes:
4x3 - 7
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! :)
Answer:
1.1
Step-by-step explanation:
If you dont want a decimal then you would just round, and get 1
Did you ever get the answer
