Question 4 Consider a consumer who consumes three goods, 1, x2 and r3. The consumer's consumption of the three goods is dependent on four variables, p, s, y and w, in the following way: a1(p, s, w, y) p*yw - sy = 0 (5) %3D x2(p, s, w, y) 3yw 1 --w = 2 (6) x3(p, s, w, y) 4ps + 3w + 2y = 9 (7) 4 Currently, p = , s = }, y = 1, and w = 2, so that the consumer is consuming 0 units of a1, 2 units of r2 and 9 units of a3. 4.1 Making use of the Implicit Function Theorem, show that the system is defined in the neighbourhood of p = }, s = }, y = 1, and w = 2 if p, s, and y are treated as endogenous variables in the model and w is treated as an exogenous variable. 4.2 Now, assuming the consumption is at the levels set out in 4.1, use calculus to approximate the new value of p if w increases by one unit. [NOTE: you may make use of Cramer's rule or use linearisation and invert the coefficient matrix]. 4.3 Assume that the following additional information becomes available about how p, y and w vary with time (t): 3 p(t) 2t s(t) 18 y(t) 2t – 5 ( – 21) + 1] w(t) %3D Using the Chain Rule, first form the Jacobian derivative matrix of the change in r1, x2 and r3 as t changes. Then evaluate the matrix at the point where t 3. I| ||
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
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