Answer:
The probability that the pirate misses the captain's ship but the captain hits = 0.514
Step-by-step explanation:
Let A be the event that the captain hits the pirate ship
The probability of the captain hitting the pirate ship, P(A) = 3/5
Let B be the event that the pirate hits the captain's ship
The probability of the pirate hitting the captain's ship P(B) = 1/7
The probability of the pirate missing the captain's ship, P'(B) = 1 - P(B)
P'(B) = 1 - 1/7 = 6/7
The probability that the pirate misses the captain's ship but the captain hits = P(A) * P(B) = 3/5 * 6/7
= 0.514
Answer:
<h3>A.
50 yards.</h3>
Step-by-step explanation:
Given the coordinates of the length of PH as P(2,55) and H(32, 15), to get the actual length of the land bridge from P to H, we will use the formula for calculating the distance between two points.
D = √(x₂-x₁)²+(y₂-y₁)²
PH = √(32-2)²+(15-55)²
PH = √(30)²+(-40)²
PH = √900+1600
PH = √2,500
PH = 50
Hence the actual length of the land bridge from P to H to the nearest yard is 50 yards.
Answer:
The nonzero vector orthogonal to the plane is <-9,-8,2>.
Step-by-step explanation:
Consider the given points are P=(0,0,1), Q=(−2,3,4), R=(−2,2,0).
The nonzero vector orthogonal to the plane through the points P,Q, and R is
Expand along row 1.
Therefore, the nonzero vector orthogonal to the plane is <-9,-8,2>.
Answer:
The greatest common factor of this would be 3x^2y
Step-by-step explanation:
In order to find this, first find the greatest common factor of the coefficients. Since 3 goes in evenly to both 15 and -18, then we know that it is a common factor.
From there we need to find the number of x's. Since the first term only has 2 x's and the second has 3, we take the lowest number. (x^2)
And since the first term has 3 y's and the second has just 1, we take the lowest number (y).
<span>Answer:
Multiple R is the correlation between y and y^
in a regression model. It is always non-negative, but has no nice interpretation as a proportion of variance, unlike its square. I can't think of too many uses for it and only know of one stat package that routinely reports it, SPSS.
Bivariate correlation only tells you about two variables at a time (though you can use partial correlation to remove other variables).</span>
