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bachelor in business administration
Polytechnic State University Sanluis
Jan-2006 - Nov-2010
CPA
Polytechnic State University
Jan-2012 - Nov-2016
Professor
Harvard Square Academy (HS2)
Mar-2012 - Present
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 The data set of Exercise 1 also includes these third- grade verbal IQ observations for males:
Let
Â
Â
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YÂ = sample mean book value
XÂ = sample mean audited value
DÂ = sample mean error
Â
|
117Â Â 103Â Â 121 |
112 |
120 |
132 |
113 |
117 |
132 |
|
149Â Â 125Â Â 131 |
136 |
107 |
108 |
113 |
136 |
114 |
|
and females: |
 |
 |
 |
 |
 |
 |
|
114Â Â 102Â Â 113 |
131 |
124 |
117 |
120 |
90 |
 |
|
114Â Â 109Â Â 102 |
114 |
127 |
127 |
103 |
 |
 |
Prior to obtaining data, denote the male values by X1,... , Xm and the female values by Y1,... , Yn. Sup- pose that the Xi s constitute a random sample from a distribution with mean m1 and standard deviation s1 and that the Yi s form a random sample (independent of the Xi  s) from another distribution with mean m2
Several different statistics for estimating the total audited (correct) value have been proposed (see Statistical Models and Analysis in Auditing, Sta- tistical Sci., 1989: 2—33). These include
Â
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Mean per unit statistic =Â NXÂ Â Â Difference statistic =Â TÂ Â -Â NDÂ Ratio statistic =Â TÂ #Â 1X/YÂ 2
If N = 5000 and T = 1,761,300, calculate the three corresponding point estimates. (The cited article dis- cusses properties of these estimators.)
and standard deviation s2.
                  6.  Consider the accompanying observations on stream
a.   Use rules of expected value to show that X - Y is an unbiased estimator of m1 - m2. Calculate the estimate for the given data.
b.   Use rules of variance from Chapter 6 to obtain an
ow (1000 s of acre-feet) recorded at a station   in
Colorado for the period April 1—August 31 over a 31-year span (from an article in the 1974 volume of Water Resources Res.).
Â
|
expression for the variance and standard  devia- |
127.96 |
210.07 |
203.24 |
108.91 |
178.21 |
|
tion (standard error) of the estimator in part  (a), |
285.37 |
100.85 |
89.59 |
185.36 |
126.94 |
|
and then compute the estimated standard  error. |
200.19 |
66.24 |
247.11 |
299.87 |
109.64 |
Â
|
125.86 |
114.79 |
109.11 |
330.33 |
85.54 |
 |
ity that a component works properly, how   can |
|
117.64 |
302.74 |
280.55 |
145.11 |
95.36 |
 |
P(system works) be expressed in terms of p?] |
|
204.91 |
311.13 |
150.58 |
262.09 |
477.08 |
c. |
Let  pˆ        be the sample proportion of successes. Is  pˆ   2 |
|
94.33 |
 |
 |
 |
 |
 |
an unbiased estimator for p2? Hint: For any rv Y, E(Y 2) = V(Y) + [E(Y)]2. |
An appropriate probability plot supports the use of the lognormal distribution (see Section 4.5) as a rea- sonable model for stream  ow.
a.   Estimate the parameters of the distribution. [Hint: Remember that X has a lognormal distri- bution with parameters m and s2 if ln(X) is nor- mally distributed with mean m and variance s2.]
b.   Use the estimates of part (a) to calculate an esti- mate of the expected value of stream ow. [Hint: What is E(X)?]
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