Answer:
If she is driving 60 mph she will save 1 hour of her time rather then going 55 mph.
Step-by-step explanation:
Answer:
Me
Step-by-step explanation:
Which characteristic of a data set makes a linear regression model unreasonable?
Answer: A correlation coefficient close to zero makes a linear regression model unreasonable.
If the correlation between the two variable is close to zero, we can not expect one variable explaining the variation in other variable. For a linear regression model to be reasonable, the most important check is to see whether the two variables are correlated. If there is correlation between the two variable, we can think of regression analysis and if there is no correlation between the two variable, it does not make sense to apply regression analysis.
Therefore, if the correlation coefficient is close to zero, the linear regression model would be unreasonable.
Answer:

Step-by-step explanation:

This is written in the standard form of a quadratic function:

where:
- ax² → quadratic term
- bx → linear term
- c → constant
You need to convert this to vertex form:

where:
To find the vertex form, you need to find the vertex. For this, use the equation for axis of symmetry, since this line passes through the vertex:

Using your original equation, identify the a, b, and c terms:

Insert the known values into the equation:

Simplify. Two negatives make a positive:

X is equal to 3 (3,y). Insert the value of x into the standard form equation and solve for y:

Simplify using PEMDAS:

The value of y is -6 (3,-6). Insert these values into the vertex form:

Insert the value of a and simplify:

:Done