OPMT 1130 Business Statistics
Myra Andrews Winter 2009
Review for Midterm
Review Exercises-OPMT 1130 Midterm pages 16-6 to 16-12
The detailed answer key is in Shareout: OPMT 1130/Myra Andrews
Information about the Midterm
90 minutes long - worth 90 ma

OPMT 1130 Business Statistics
Myra Andrews, Stephen Reid Winter 2012
Review for Midterm
Review Questions See the handout in Shareout called Midterm Exercises. *A detailed answer key is in Shareout OPMT/1130/Myra Andrews Information about the Midterm Base

Session 13
TDMT 2203
Learning Objectives At the end of this session you should be able to: 1. State the arguments and counterarguments of price and entry regulation of an industry. 2. Explain why firms would want to be regulated. 3. Illustrate how the ind

Session 12
TDMT 2203
Learning Objectives After this session you should be able to: 1. Explain with the highway-widening example why it is difficult to measure net social benefit. 2. List the steps of Cost Benefit Analysis (CBA). 3. Differentiate between a

Session 11
TDMT 2203
Learning Objectives At the end of this session you should be able to: 1. Distinguish between the private and social costs of congestion. 2. Explain why marginal and average costs rise with congestion. 3. Illustrate how a congestion to

FMGT3550 December 2012 Final Exam Formula Sheet Yield to maturity K d = Yield (1 T) preferred stock K p = Dp Pp K p =Dp /( P p F)
K p =[Dp / P p ]/(1 F) Dividendgrowth model
new coomonstock
Profitability Index = PI = PV (Cash Inflows) PV (Cash Outflows)

Midterm Review Lecture 1. A class of 25 students took a statistics test. 10 students had an average mark of 72. The other students had an average mark of 65. What is the average mark of the whole class? 2. The uncertainty is the stock market has led Sam t

OPMT 1130 Review exercises
Review Exercises Midterm 1. An investor bought a total of 1,000 shares of QT Resources. In January, he purchased 300 shares and paid $10.00 per share, in February he purchased 200 shares at $11.00/share. He bought the rest of th

Lecture 11: Poisson Probability Distribution
Examples where it applies: 1. The number of car accidents in the lower mainland per day. 2. The number of spam emails that a computer user will receive per week. 3. The number of phone calls to a call center pe