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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.
a, b,c are in h.p prove that a/b+c-a, b/a+c-b, c/a+b-c are in h.p To prove: (b+c-a)/a; (a+c-b)/b; (a+b-c)/c are in A.P or (b+c)/a; (a+c)/b; (a+b)/c are in A.P or 1/a; 1
Derivatives of Exponential and Logarithm Functions : The next set of functions which we desire to take a look at are exponential & logarithm functions. The most common exponentia
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Linear Approximation Method This is a rough and ready method of interpolation and is best used when the series moves in predicted interval
Multiplication Rule: Dependent Events The joint probability of two events A and B which are dependent is equal to the probability of A multiplied by the probability of B given
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