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Answer:
because they are opposite sides of a parallelogram.
Step-by-step explanation:
First of all, let us have a look at the definition of a parallelogram.
<em>A parallelogram is a closed 4 sided figure (i.e. a quadrilateral) made up with two pairs of straight lines such that the two pairs are parallel and equal to each other.</em>
<em></em>
For example, let us consider a quadrilateral ABCD as attached in the diagram in answer area.
The two pair of lines are:
AB, DC and BC, AD
For ABCD to be a parallelogram, the lines
AB and DC must be parallel to each other and AB = DC
AND
BC and AD must be parallel to each other and BC = DA
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In the given question, we are given that the quadrilateral MNOP is a parallelogram.
The two pairs opposite lines are OP, NM and PM, ON.
As per the definition of a parallelogram,
OP and NM must be <em>parallel and equal </em>to each other.
AND
PM and ON must be <em>parallel and equal </em>to each other.
.
Hence proved.
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%