Your name:
Fall 2005
S370
Midterm 1
Prof. Alexeev
1. A clothes store manager has sales data of trouser sizes for the last month's sales. Which
measure of central tendency should the manager use, if the manager is interested in the
most sellable size?
A. M
Fall 2008
S370
Midterm 2
(The test has 18 problems)
Prof. Alexeev
1. As the random sample size increases,
A. The sample approaches the normal distribution.
B. The population approaches the distribution of a normal random variable.
C. The sampling distribu
Fall 2004
S370
Midterm 2
Prof. Alexeev
1. If the population from which a random sample is taken has any distribution other than
normal, then the distribution of sample mean is:
A.
B.
C.
D.
E.
Similar to the distribution of the original population for larg
Fall 2005
S370
Midterm 2
Prof. Alexeev
1. Consider the following statements:
I. When the sample is small and the population is normal, sample mean is distributed
normally;
II. When the sample is large, sample mean is approximately normally distributed;
II
FALL 2009
STATISTICAL ANALYSIS FOR BUSINESS AND ECONOMICS
S370 Honors section 8906
MW 2:30 pm - 3:45 pm; Woodburn Hall 002 & Wylie Hall 125 (Computer lab)
CLASS HOMEPAGE: http:/mypage.iu.edu/~malexeev/s370home.html
INSTRUCTOR:
OFFICE HOURS:
Prof. Michael
FORMULAS
Position of Pth percentile is given by (n+1)P/100
Population mean: =
_
N
xi / N
i
1
_
N
Sample mean: X x i /n
i
1
N
N
i
1
i
1
Weighted sample mean: X w i x i / w i
.
Geometric mean of a set of N observations: GM = N x 1 x 2 x N ; It follows that
Sample final examination questions related to the post-Midterm 2 material
Note: even though questions 16-18 below are not multiple-choice, all questions on
this years final exam will be multiple-choice.
USE THE FOLLOWING INFORMATION TO ANSWER THE NEXT THR
Your name:
Fall 2008
S370
Midterm 1
Prof. Alexeev
1. A survey of firms includes their industry codes that range from 1 to 4. E.g.,
manufacturing firms are coded as 1, service firms are coded as 2, etc. This is an example
of which scale of measurement?
*A.
Handout on functions of a random variable
and joint distributions of random variables
(Prof. Alexeev, S370 Honors Section)
Sometimes it is useful to consider random variables that are functions of other random variables.
For example, consider a part-time
S370 Fall 2009
Midterm 1
Prof. Alexeev
USE THE FOLLOWING INFORMATION TO ANSWER QUESTIONS 1-4
The following table presents Excel-generated descriptive statistics of the secondary
school enrollment rates (in %) in 2000 in 13 European economies in transition
Suppose I invested 100 into a risky mutual fund that has returned 50% in year 1 [that is
my investment after the first year had grown to 100*(1+0.5)=100*1.5=150], 10% in year
2 and 60% in year 3. Therefore, over three years, my investment has grown to:
10
Your name:
Fall 2004
S370
Midterm 1
Prof. Alexeev
1. Todays exam starts at 13:00 hours and lasts for 75 minutes. The first and second
numbers are examples of, respectively, the following scales of measurement:
A. Interval and interval
C. Interval and rati
lawschool year
Alabama
American U
Arizona
Arizona St
Baylor
Boston Univ
Brooklyn L
BYU
CaliforniaCaliforniaCaliforniaCalifornia
Catholic
Chicago
Cincinnati
Colorado
Columbia
Connecticu
Cornell
Denver
Duke
Emory
Florida
Florida Sta
Fordham
George Ma
George
FORMULAS
Law of total probability: P(A) = P(A|B)P(B) + P(A|notB)P(notB)
Bayes Theorem: P(B | A)
P(A | B)P(B)
P(A | B)P(B) P(A | notB)P(notB)
BINOMDIST(# of successes, # of trials, probability of success, cumulative) returns the
binomial cumulative distri