Answer:
See graph in attachment.
Step-by-step explanation:
The graph of is a parabola that has its vertex at the origin.
The equation of the transformed graph is
The vertex of this transformed function is
Drag the blue graph up so that the vertex will now be at (4,3).
See graph in attachment.
Answer:
x ≈ 29.4 ft
Step-by-step explanation:
The model is a right triangle.
Using the tangent ratio
tan40° = =
( multiply both sides by 35 )
35 × tan40° = x , then
x ≈ 29.4 ft ( to 1 dec. place )
Answer:
a)
b) The accountant should not question the voucher as the request is much higher than expected.
c) We can add the following variables
d) The percentage of variation in the trip cost that can be explained by the model = (0.64)^2 =0.4096 or 40.96%
A. Type of travel (air/car)
B. Gender of the executive (male/female)
The last option is not too important since we are analyzing the traveling executives not the type of business
Step-by-step explanation:
Part a
For this case we have the multiple regression model given by:
Where represent the number of days on the road and
the distance traveled in miles.
And we want to find the expected amount from a 340-mile trip that took her out of town for 5 days, so we just need to replace x1= 5 and x2=340 and we got:
Part b
The expected value taking in count that x1 = 5 and y = 340 is:
And the difference from the obtained value is : 685-441.50=243.5
So then the correct answer would be:
The accountant should not question the voucher as the request is much higher than expected.
Part c
We can add the following variables
A. Type of travel (air/car)
B. Gender of the executive (male/female)
The last option is not too important since we are analyzing the traveling executives not the type of business
Part d
The correlation coefficient is a "statistical measure that calculates the strength of the relationship between the relative movements of two variables". It's denoted by r and its always between -1 and 1.
The coefficient of determination "is a measure used in statistical analysis that assesses how well a model explains and predicts future outcomes. It is indicative of the level of explained variability in the data set".
The percentage of variation in the trip cost that can be explained by the model = (0.64)^2 =0.4096 or 40.96%