Biovail Corporation
Revenue Recognizing and FOB Sales Accounting
Assignment Question 1.
How many truckloads of product are actually required to carry $10 million of product? Show
Calculations.
From the case we know:
1.
2.
3.
4.
Interior Dimension of the t

MBAC6031 Quantitative Methods Midterm Exam
Fall 2016
First Name:
Last Name :
Nimisha
Kumari
Instructions
You may add more worksheets but do not change the names of
the Question worksheets included here.
You may add functions and data to the Question works

Z a/2value for standard distribution
90%( a=0.1, a/2= 0.05
95%(a/2=0.025)
1.644854
-1.959964
99% -2.575829
1.645
1.96
2.576
Normality of p
n*pi>=10 n*(1-pi)>=10
Sample size to estimate mean
n=(z*sigma/e)square
t value when sigma is unknown
95%-since it co

MBAC6031 Quantitative Methods Midterm Exam
Fall 2016
First Name:
Last Name :
Honor Code: On my honor, as a University of Colorado
Boulder student, I have neither given
nor received unauthorized assistance
on this exam.
Initials:
Your initials indicate tha

Intercorporate Investments
Coca Cola
Coca-Cola has substantial investment in equity and debt securities of other companies. Moreover, certain
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MBAC6031 Quantitative Methods Midterm Exam
Fall 2015
First Name:
Last Name :
Honor Code: On my honor, as a University of Colorado
Boulder student, I have neither given
nor received unauthorized assistance
on this exam.
Initials:
Your initials indicate tha

Preliminary Exam - Econometrics - January 2013
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Directions: Answer any four of the following five problems.
1.
Match the concept to the definition or notation:
_a.
_b.
_c.
_d.
_e.
_f.
_g.
_h.
_i.
_j.
_k.
Variance-covariance matrix
Cramer-Rao lower b

Prelim in Econometrics, January 2008
1.
Match the description in the column on the left to the word or expression in the
column on the right. (In your bluebooks, your answer should look like, e.g., 1-M, 2P, )-D, etc.).
plim s) )
1
2 For ,8 a sequence of r

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Econometrics - Part II
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Question 1. Consider a set of M 2 linear regressions. The regressand on the mth regression is denoted
by Ym R. There are qm N regressors on the mth regression, that are denoted by Xm,1 , Xm,qm . The
unob

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Jan. 2012
The Statistics Part
Answer all four questions to the best of your ability.
Read the whole exam before attempting any answers.
If you are uncertain about something you write, tell us.
1. Consider the density functio

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August 2007
Part I
Choose three of the four problems in this part.
1a.
What is random variable? and what role do they play in statistics? (1-2
paragraphs).
b.
In 7818 you studied sample spaces, outcomes, events, probability and prob

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Allocate your time appropriately between the two halves of the prelim (this
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This, the rst half of the prelim, has two questions, the latter having six
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Preliminary Exam
Econometrics
Part I
January 2015
1. The joint density of the random variables \ ] is given by
0 B C
" #! B
"! B #!
#&
B
B# C B
a. Find the marginal density of \ .
b. Find the conditional density of ] given \
c. Find T ] %l\ "#
2. The in

Preliminary Exam
Econometrics - Part II
August 2014
Question 1. Consider the regression model
Y = X + ,
(1)
where Y is a scalar regressand, X is a scalar non-stochastic regressor, is an unknown parameter to be
estimated based on a sample cfw_Yt , Xt nt=1

First half of econometrics prelim, Fall 2009
Allocate you time appropriately between the two halves of the exam (this half and
the other half). You will likely not be able to finish this half of the exam, do not
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Preliminary Exam
Econometrics - Part II
January 2015
Question 1. Let Xi =
Yi
Zi
0
for i = 1, , n be a sequence of independent and identically distributed
random vectors, where Zi represents the education of individual i and Yi = 1 if individual i has a jo

Econometrics Preliminary Exam Part II August 2010
1. Suppose the demand and supply equations in the market for gasoline have the following form
(all variables are in deviations from their means):
(1) Qt = Pt + ut (demand) < 0
(2) Qt = Pt +Ot + vt (supply)

Preliminary Exam Econometrics January 2011
Part 2
1.
Partition the k-variable model as, y = X11 + X22 +, where X1 contains k-r variables and X2 has
r variables. The Frisch-Waugh theorem establishes that the least squares estimator of 2 can be
estimated by

Preliminary Exam
Econometrics
August 2014
Part I
Directions: answer all questions. Show all work.
1. Consider the gamma distribution for a continuous random variable, ] K ),
) !, ! with density function
0 C
) )C "
/ C C!
>
1
where >() x when is an integ

Prelim in Statistics/Econometrics
August, 2012
Part I
Answer any four (4) of the following five questions.
1. Let the joint probability distribution of \ ] be given by
]
\
"
!
a)
b)
c)
d)
e)
f)
"
#)
#)
!
")
$)
Is this a proper probability distribution? Wh

Second Half Econometrics Prelim
1.
Fall 2009
Given the linear regression model
C \" %
where C and % are 8 ", \ is an 8 O matrix whose first column is a column of ones
(3), and " is a O " vector of constants.
a) List the assumptions about \ and % that are

Preliminary Exam Econometrics August 2012
Part 2
1. A. Let u be an mx1 random vector of normally distributed random variables with expectation 0, and
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First half of econometrics prelim, January 2010
Allocate your time appropriately between the two halves of the exam (this
half, and the other half).
This, the rst half of the prelim, has four questions. Answer all four questions
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Preliminary Exam Econometrics January 2014
Part 2
-1
1. Let M= I X(XX) X where I is the identity matrix of order n, X is the nxk matrix of
observations on explanatory variables, and y is the nx1 vector of observations on the
dependent variable in the mode

Preliminary Exam
Econometrics - Part II
January 2016
Question 1. Consider the following regression model,
Yi = Xi + i for i = 1, , n
(1)
where B RK , Xi is a conformable vector of regressors, and i is an unobserved error with E(i |Xi ) = 0,
V (i |Xi ) = 2

Preliminary Exam Econometrics August 2013
Part 2
1. For the model, y = X + where y and are nx1 vectors and X is an nxk matrix of explanatory
variables,
a. present the assumptions (without interpretation or explanation) of the classical
regression model.
b