Answer:
E(x) = 1.43 (Approx)
Step-by-step explanation:
Given:
Total number of camera = 7
Defective camera = 5
Sample selected = 2
Computation:
when x = 0
P(x=0) = 2/7 × 1/6 = 2/42
P(x=1) = [2/7 × 5/6] + [5/7 × 2/6] = 20/42
P(x=2) = 5/7 × 4/6 = 20/42
So,
E(x) = [0×2/42] + [1×20/42] + [2×20/42]
E(x) = 1.43 (Approx)
Answer:
f(x) = -3(x+3)(x-1)
Step-by-step explanation:
x = -3 & 1; f(x) = 9
f(x) = a(x-r1)(x-r2)
f(0) = a(x-r1)(x-r2) = 9; 9 = a(0-(-3))(0-1)
9 = a(3)(-1); 9 = a(-3)
a = -3
f(x) = -3(x+3)(x-1)
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Area=1/2 times base times height
note:bh=base times height
a=1/2bh
b=width
h=-4+2w
h=2w-4
subsitute
a=1/2w(2w-4)
a=1/2(2s^2-4w)
a=w^2-2w
a=63
63=w^2-2w
subtract 63 from both sdies
0=w^2-2w-63
factor
find what 2 numbers multiply to get -63 and add to get -2
the numbers are -9 and 7
so
0=(w-9)(w+7)
if xy=0 then x and/or y=0
so
w-9=0
w+7=0
solve each
w-9=0
add 9 to both sdies
w=9
w+7=0
subtract 7 from both sides
w=-7
width cannot be negative so this can be discarded
width=9
subsitute
l=2w-4
l=2(9)-4
l=18-4
l=14
legnth=14 in
width/base=9 in
Answer:
The residual value is -0.75
Step-by-step explanation:
we know that
The residual value is the observed value minus the predicted value.
RESIDUAL VALUE=[OBSERVED VALUE-PREDICTED VALUE]
where
Predicted value.--> the predicted value given the current regression equation
Observed value. --> The observed value for the dependent variable.
in this problem
we have the point (1,4)
so
The observed value is 4
<em>Find the predicted value for x=1 </em>
predicted value is 4.75
so
RESIDUAL VALUE=(4-4.75)=-0.75
