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Exponential and Geometric Model
Exponential model
y = abx
Take log of both sides
log y = log a + log bx
log y = log a + xlog b
Assume log y = Y and log a = A and log b = B
Hence we get Y = A + Bx. It is a linear regression model
Geometric model
y = axb
By using the similar technique as above
log y = log a + b log x
Y = A + bX
Whereas Y = log y
A = log a
X = log x
By using linear regression technique or the method of least squares, it is possible to calculate the value of a and b.
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Liner Regression The calculations for our sample size n = 10 are described below. The linear regression model is y = a + bx Table: Distance x miles
Domain of a Vector Function There is a Vector function of a single variable in R 2 and R 3 have the form, r → (t) = {f (t), g(t)} r → (t) = {f (t) , g(t), h(t)} co
Use the definition of the limit to prove the given limit. Solution Let ε> 0 is any number then we have to find a number δ > 0 so that the following will be true. |
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The distribution of sample means is not always a normal distribution. Under what circumstances is the distribution of sample means not normal?
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Decision-Making Under Conditions of Uncertainty With decision making under uncertainty, the decision maker is aware of different possible states of nature, but has insufficient
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