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Variance
Consider the example of investment opportunities. The expected gains were Rs.114 and Rs.81 respectively. The fact is that an investor also looks at the dispersion before coming to a decision.
The dispersion of opportunity 1 is far greater than that of opportunity 2. This might alarm the investor.
In this example, it might be worthwhile to compute the coefficient of variation.
For opportunity 1, this works out to be
= (42/114) x 100 = 36.84%
For opportunity 2, this works out to be
= (29.14/81) x 100 = 35.97%
The investor may regard both opportunities homogeneous in this regard and therefore find opportunity 1 more attractive (because of the higher expected returns).
Constrcut the adjacency matrix and the adjacency lists for the graph G belowr.
The 't' distribution is a theoretical probability distribution. The 't' distribution is symmetrical, bell-shaped, and to some extent similar to the standard normal curve. It has an
i dont know how to do it
Eddie mkes $15.75 per hour. Estimate how much Eddie will make per year if he works 40 hours per week and 50 weeks per year.
condition for linearly independent
Leo works at the Bagel Shop after school and on Saturdays. He is paid $4.00 per hour after school and $5.00 per hour on Saturday. Last week Leo worked a total of 12 hours and made
x2+y2 r=12
Unit Vector and Zero Vectors Unit Vector Any vector along with magnitude of 1, that is || u → || = 1, is called a unit vector. Zero Vectors The vector w → = (
We will begin this chapter by looking at integer exponents. Actually, initially we will suppose that the exponents are +ve as well. We will look at zero & negative exponents in a
1. If the equation has any fractions employ the least common denominator to apparent the fractions. We will do this through multiplying both sides of the equation by the LCD. Al
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