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Standardizing Normal Variables
Suppose we have a normal population. We can represent it by a normal variable X. Further, we can convert any value of X into a corresponding value Z of the standard normal variable, by using the formula
Where,
X = the value of any random variable
m = the mean of the distribution of the random variable
s = the standard deviation of the distribution
Z = the number of standard deviations from X to the mean of the distribution and is known as the Z score or standard score.
If the diameter of a circle is tripled times, the circumference is a. multiplied by 3. b. multiplied by 6. c. multiplied by 9. d. multiplied by 12. a. The formula fo
f Y is a discrete random variable with expected value E[Y ] = µ and if X = a + bY , prove that Var (X) = b2Var (Y ) .
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Initial Conditions and Boundary Conditions In many problems on integration, an initial condition (y = y 0 when x = 0) or a boundary condition (y = y
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Chain Rule : If f(x) and g(x) are both differentiable functions and we describe F(x) = (f. g)(x) so the derivative of F(x) is F′(x) = f ′(g(x)) g′(x). Proof We will s
Consider a database whose universe is a finite set of vertices V and whose unique relation .E is binary and encodes the edges of an undirected (resp., directed) graph G: (V, E). Ea
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