Line 9: Line 9:
 
<math>E(X)= \sum_{k=0}^n kr^k</math><br>
 
<math>E(X)= \sum_{k=0}^n kr^k</math><br>
 
Since<br>
 
Since<br>
<math>\frac{1-r^(n+1)}{1-r}= \sum_{k=0}^n r^k</math><br>
+
<math>\frac{1-r^{n+1}}{1-r}= \sum_{k=0}^n r^k</math><br>
 
Taking the derivative <math>\frac{d}{dr}</math> of both sides will yield<br>
 
Taking the derivative <math>\frac{d}{dr}</math> of both sides will yield<br>
<math>\frac{-(n+1)r^n(1-r)+(1-r^(n+1))}{(1-r)^2}= \sum_{k=0}^n kr^(k-1)</math><br>
+
<math>\frac{-(n+1)r^n(1-r)+(1-r^{n+1})}{(1-r)^2}= \sum_{k=0}^n kr^(k-1)</math><br>
 
Multiply both sides by r to see the form of the expected value in the problem:<br>
 
Multiply both sides by r to see the form of the expected value in the problem:<br>
<math>r\frac{-(n+1)r^n(1-r)+(1-r^(n+1))}{(1-r)^2}= \sum_{k=0}^n kr^(k)</math><br>
+
<math>r\frac{-(n+1)r^n(1-r)+(1-r^{n+1})}{(1-r)^2}= \sum_{k=0}^n kr^(k)</math><br>
 
This value is the mean, which, when 100 widgets is inserted in for n and .9 is inserted in for r, can be found to equal 90 widgets, as expected.<p>
 
This value is the mean, which, when 100 widgets is inserted in for n and .9 is inserted in for r, can be found to equal 90 widgets, as expected.<p>
  
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can be used.<br>
 
can be used.<br>
 
<math>E(x^2)</math> can be expanded to find that<br>
 
<math>E(x^2)</math> can be expanded to find that<br>
<math>VAR=(\sum_{k=0}^n (k^2)(r^k))-(E(x))^2</math><br>
+
<math>VAR=(\sum_{k=0}^n k^2r^k)-(E(x))^2</math><br>
 
The formula<br>
 
The formula<br>
<math>r\frac{-(n+1)(r^n)(1-r)+(1-r^(n+1))}{(1-r)^2}= \sum_{k=0}^n kr^(k)</math><br>
+
<math>r\frac{-(n+1)r^n(1-r)+(1-r^{n+1})}{(1-r)^2}= \sum_{k=0}^n kr^(k)</math><br>
 
can be used to derive the formula for <math>E(x^2)</math>.  To do this, take the derivative <math>\frac{d}{dr}</math> of both sides to find that<br>
 
can be used to derive the formula for <math>E(x^2)</math>.  To do this, take the derivative <math>\frac{d}{dr}</math> of both sides to find that<br>
<math>\frac{-(n+1)r^n(1-r)+(1-r^(n+1))}{(1-r)^2}<\math><br><math>+r\frac{((1-r)^2)(-n(n+1)r^(n-1)+n(n+1)(r^n))-(-(n+1)(r^n)(1-r)+(1-r^(n+1)))(-2+2r)}{(1-r)^4}= \sum_{k=0}^n (k^2)r^(k-1)</math><br>
+
<math>\frac{-(n+1)r^n(1-r)+(1-r^{n+1})}{(1-r)^2}</math><br><math>+r\frac{((1-r)^2)(-n(n+1)r^{n-1}+n(n+1)r^n)-(-(n+1)r^n(1-r)+(1-r^{n+1}))(-2+2r)}{(1-r)^4}= \sum_{k=0}^n (k^2)r^{k-1}</math><br>
 
Multiplying both sides by r yields the expression for <math>E(x^2)</math> to be<br>
 
Multiplying both sides by r yields the expression for <math>E(x^2)</math> to be<br>
<math>r\frac{-(n+1)r^n(1-r)+(1-r^(n+1))}{(1-r)^2}<\math><br><math>+(r^2)\frac{((1-r)^2)(-n(n+1)r^(n-1)+n(n+1)(r^n))-(-(n+1)(r^n)(1-r)+(1-r^(n+1)))(-2+2r)}{(1-r)^4}= \sum_{k=0}^n (k^2)(r^k)</math><br>
+
<math>r\frac{-(n+1)r^n(1-r)+(1-r^{n+1})}{(1-r)^2}</math><br><math>+r^2\frac{((1-r)^2)(-n(n+1)r^{n-1}+n(n+1)r^n)-(-(n+1)r^n(1-r)+(1-r^{n+1}))(-2+2r)}{(1-r)^4}= \sum_{k=0}^n k^2r^k</math><br>
 
Therefore, the formula for the variance is given by <br>
 
Therefore, the formula for the variance is given by <br>
<math>VAR=r\frac{-(n+1)r^n(1-r)+(1-r^(n+1))}{(1-r)^2}<\math><br><math>+(r^2)\frac{((1-r)^2)(-n(n+1)r^(n-1)+n(n+1)(r^n))-(-(n+1)(r^n)(1-r)+(1-r^(n+1)))(-2+2r)}{(1-r)^4}-(r^2)(\frac{-(n+1)r^n(1-r)+(1-r^(n+1))}{(1-r)^2})^2</math><br>
+
<math>VAR=r\frac{-(n+1)r^n(1-r)+(1-r^{n+1})}{(1-r)^2}</math><br><math>+r^2\frac{((1-r)^2)(-n(n+1)r^{n-1}+n(n+1)r^n)-(-(n+1)r^n(1-r)+(1-r^{n+1}))(-2+2r)}{(1-r)^4}-r^2(\frac{-(n+1)r^n(1-r)+(1-r^{n+1})}{(1-r)^2})^2</math><br>
 
When 100 is inserted in for n and .9 is inserted in for r, the variance can be found to equal .
 
When 100 is inserted in for n and .9 is inserted in for r, the variance can be found to equal .
  

Revision as of 15:12, 21 February 2013

Dude91's Third Bonus Point Problem

Question:

Bob owns a company that produces n=100 widgets each day. The probability that a widget is produced without defect is r=.9. What is the mean and the variance of the process Bob uses?


Solution:

If X is taken to be the number of correctly produced widgets made each day, then the expected value of X is
$ E(X)= \sum_{k=0}^n kr^k $
Since
$ \frac{1-r^{n+1}}{1-r}= \sum_{k=0}^n r^k $
Taking the derivative $ \frac{d}{dr} $ of both sides will yield
$ \frac{-(n+1)r^n(1-r)+(1-r^{n+1})}{(1-r)^2}= \sum_{k=0}^n kr^(k-1) $
Multiply both sides by r to see the form of the expected value in the problem:
$ r\frac{-(n+1)r^n(1-r)+(1-r^{n+1})}{(1-r)^2}= \sum_{k=0}^n kr^(k) $

This value is the mean, which, when 100 widgets is inserted in for n and .9 is inserted in for r, can be found to equal 90 widgets, as expected.

To find the variance, the formula
$ VAR=E(x^2)-(E(x))^2 $
can be used.
$ E(x^2) $ can be expanded to find that
$ VAR=(\sum_{k=0}^n k^2r^k)-(E(x))^2 $
The formula
$ r\frac{-(n+1)r^n(1-r)+(1-r^{n+1})}{(1-r)^2}= \sum_{k=0}^n kr^(k) $
can be used to derive the formula for $ E(x^2) $. To do this, take the derivative $ \frac{d}{dr} $ of both sides to find that
$ \frac{-(n+1)r^n(1-r)+(1-r^{n+1})}{(1-r)^2} $
$ +r\frac{((1-r)^2)(-n(n+1)r^{n-1}+n(n+1)r^n)-(-(n+1)r^n(1-r)+(1-r^{n+1}))(-2+2r)}{(1-r)^4}= \sum_{k=0}^n (k^2)r^{k-1} $
Multiplying both sides by r yields the expression for $ E(x^2) $ to be
$ r\frac{-(n+1)r^n(1-r)+(1-r^{n+1})}{(1-r)^2} $
$ +r^2\frac{((1-r)^2)(-n(n+1)r^{n-1}+n(n+1)r^n)-(-(n+1)r^n(1-r)+(1-r^{n+1}))(-2+2r)}{(1-r)^4}= \sum_{k=0}^n k^2r^k $
Therefore, the formula for the variance is given by
$ VAR=r\frac{-(n+1)r^n(1-r)+(1-r^{n+1})}{(1-r)^2} $
$ +r^2\frac{((1-r)^2)(-n(n+1)r^{n-1}+n(n+1)r^n)-(-(n+1)r^n(1-r)+(1-r^{n+1}))(-2+2r)}{(1-r)^4}-r^2(\frac{-(n+1)r^n(1-r)+(1-r^{n+1})}{(1-r)^2})^2 $
When 100 is inserted in for n and .9 is inserted in for r, the variance can be found to equal .


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