By definition, the unit vector of v = (a,b) is
Therefore,
The unit vector of v₁ = (3,5) in the direction of |v₁| s
(3,5)/√[3² + 5²]
= (3,5)/√34
The unit vector of v₂ in the direction of |v₂| is
(-4,7)/√[(-4)² + 7²]
= (-4,7)/√65
Answer:
The unit vector of v₁ in the direction of |v₁} is
The unit vector of v₂ in the directin of |v₂| is
Answer:
(E) The bias will decrease and the variance will decrease.
Step-by-step explanation:
Given that researchers working the mean weight of a random sample of 800 carry-on bags to e the airline.
We have to find out the effect of increasing the sample size on variance and bias.
We know as per central limit theorem, sample mean follows a normal distribution with mean = sample mean
and std deviation of sample mean = std error = 
Thus std error the square root of variance is inversely proportional to the square root of sample size.
Also whenever we increase sample size the chances of bias would decrease as the sample size becomes larger
So correct answer is both bias and variation will decrease.
(E) The bias will decrease and the variance will decrease.
Answer:
Return on investment (ROI) = 7%
Step-by-step explanation:
Given:
Amount invested = $10,000
Total amount get (refund) = $10,700
Find:
Return on investment (ROI) = ?
Computation:
Amount Return = Total amount get (refund) - Amount invested
Amount Return = $10,700 - $10,000
Amount Return = $700
![Return\ on\ investment \ (ROI) = [\frac{Amount\ Return}{Amount\ invested} ]100\\\\Return\ on\ investment \ (ROI) = [\frac{700}{10,000} ]100 \\\\ Return\ on\ investment \ (ROI) =7](https://tex.z-dn.net/?f=Return%5C%20on%5C%20investment%20%5C%20%28ROI%29%20%3D%20%5B%5Cfrac%7BAmount%5C%20Return%7D%7BAmount%5C%20invested%7D%20%5D100%5C%5C%5C%5CReturn%5C%20on%5C%20investment%20%5C%20%28ROI%29%20%3D%20%5B%5Cfrac%7B700%7D%7B10%2C000%7D%20%5D100%20%5C%5C%5C%5C%20Return%5C%20on%5C%20investment%20%5C%20%28ROI%29%20%3D7)
Return on investment (ROI) = 7%
Answer:
Quadrant 1
Step-by-step explanation:
The co-ordinates given match up exactly to co-ordinate 1 due to all the numbers given being positive.
There are 4 quadrants. Quadrant 1, 2, 3, and 4.
