Answer:
Option A
Step-by-step explanation:
Given that A linear model is given for the data in the table: y=1.25x+2.
Let us write observed values for each x and also the predicted values as per equation.
x 2 3 4 8 10 16 20 24 Total
y((O) 3 4 7 12 16 22 28 30
y(P) 4.5 5.75 7 12 14.5 22 27 32
DEv 1.5 1.75 0 0 1.5 0 1 2 7 75
where y(0) represents observed y or y in the table given
y(P) gives values of y predicted as per the equation 1.25x+2
Dev represents the absolute difference
Hence answer is option
A.7.75
Answer:
200
Step-by-step explanation:
100+
100
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200
Answer:
-53
/14
Step-by-step explanation:
D) (-2,3)
-2 is the x-value
3 is the y-value
If you look at the graph on the x-axis (horizontal line) the numbers are increasing and decreasing by 1.
Since the point of intersection (big blue dot) is on the left side of 0, it falls directly at the -2 mark
As for the y-axis (vertical lines) the numbers also increase and decrease by 1. The point of intersection falls above 0 at +3
Therefore your point of intersection is (-2,3)
Answer:
ans=13.59%
Step-by-step explanation:
The 68-95-99.7 rule states that, when X is an observation from a random bell-shaped (normally distributed) value with mean 
and standard deviation 
, we have these following probabilities
In our problem, we have that:
The distribution of the number of months in service for the fleet of cars is bell-shaped and has a mean of 53 months and a standard deviation of 11 months
So 
So:
-----------
-----
What is the approximate percentage of cars that remain in service between 64 and 75 months?
Between 64 and 75 minutes is between one and two standard deviations above the mean.
We have 
subtracted by is the percentage of cars that remain in service between one and two standard deviation, both above and below the mean.
To find just the percentage above the mean, we divide this value by 2
So:
The approximate percentage of cars that remain in service between 64 and 75 months is 13.59%.
