Weighted Voting Problems. Problem 1 1. The disciplinary board at PU is composed of 5 members, two of whom must be faculty and three of whom must be students.

Slides:



Advertisements
Similar presentations
Chapter 11: Weighted Voting Systems Lesson Plan
Advertisements

Chapter 2: Weighted Voting Systems
Counting and Factorial. Factorial Written n!, the product of all positive integers less than and equal to n. Ex: Evaluate.
Weighted Voting, Algorithms and Voting Power
MAT 105 Spring  In many voting systems, the voters are not treated equally  Juries: If one voter votes “not guilty,” then the result is “not guilty”
Weighted Voting When we try to make collective decisions, it is only natural to consider how things are done in society. We are familiar with voting for.
Chapter 11: Weighted Voting Systems Lesson Plan
Presented by: Katherine Goulde
Chapter 13 – Weighted Voting Part 4 Appropriate applications of measures of power Minimal winning coalitions Classification of weighted voting systems.
Math for Liberal Studies.  In many voting systems, the voters are not treated equally  Juries: If one voter votes “not guilty,” then the result is “not.
V OTING W EIGHTS SYSTEM Chapter 12 sec 3.. V OTING P OWER Def. The probability that a single vote is decisive Is affected by the rule for aggregating.
DM.8. Is a set of numbers that are listed in the following format: [ quota: weight of voter 1, weight of voter 2,…weight of voter 3] Ex: [8:5,4,3,2]
§ The Banzhaf Power Index
1 Message to the user... The most effective way to use a PowerPoint slide show is to go to “SLIDE SHOW” on the top of the toolbar, and choose “VIEW SHOW”
Excursions in Modern Mathematics Sixth Edition
Warm-Up Grab a sheet of multiple choice questions and work on those!
 Symbolic manipulation with artificial applications …  With little or no connection to the real world…
§ 2.1 Weighted Voting Systems. Weighted Voting  So far we have discussed voting methods in which every individual’s vote is considered equal--these methods.
Homework Discussion Read Pages 48 – 62 Page 72: 1 – 4, 6 TEST 1 ON THURSDAY FEBRUARY 8 –The test will cover sections 1.1 – 1.6, and 2.1 – 2.3 in the textbook.
§ The Shapley-Shubik Power Index
Objective: Learn to multiply and divide integers.
Applications of Consecutive Integers
Excursions in Modern Mathematics, 7e: Copyright © 2010 Pearson Education, Inc. 2 The Mathematics of Power 2.1An Introduction to Weighted Voting.
6-5 Data Distributions Objective
Calculating Power in Larger Systems Nominal, Banzhaf and Shapley-Shubik.
Chapter 13 – Weighted Voting
Chapter 13: Weighted Voting Banzhaf Power Index Shapley-Shubik Power Index Equivalent Systems Examples.
Weighted Voting Systems Brian Carrico. What is a weighted voting system?  A weighted voting system is a decision making procedure in which the participants.
Investigation #1 Factors and Products.
Do Now: Pass out calculators. 1. Compare and contrast factoring: 6x 2 – x – 2 with factoring x 2 – x – 2 Factor both of the problems above. Write a few.
 Law Making Body of the US government  Senate  2 Senators per State  House of Representatives  Number of representatives depend on Population.
CLASS OPENER: Is the given sequence arithmetic, if so what is the common difference? 1.1,4,9,16… 2.-21, -18, -15, -12… 3.97, 86, 75, 64… 4.0, 1, 3, 6,
MATH 104 Chapter 1 Reasoning.
Excursions in Modern Mathematics, 7e: Copyright © 2010 Pearson Education, Inc. 2 The Mathematics of Power 2.1An Introduction to Weighted Voting.
Math for Liberal Studies.  We want to measure the influence each voter has  As we have seen, the number of votes you have doesn’t always reflect how.
Weighted Voting Systems
Lesson 6.8A: The Binomial Theorem OBJECTIVES:  To evaluate a binomial coefficient  To expand a binomial raised to a power.
Chapter 7 Continuous Distributions Notes page 137.
Manipulating the Quota in Weighted Voting Games (M. Zuckerman, P. Faliszewski, Y. Bachrach, and E. Elkind) ‏ Presented by: Sen Li Software Technologies.
Excursions in Modern Mathematics, 7e: Copyright © 2010 Pearson Education, Inc. 2 The Mathematics of Power 2.1An Introduction to Weighted Voting.
8-5 Estimating mean differences. Comparing two populations Are two populations different? Really? Just a little? What if I wanted to compare the mean.
Discrete and Continuous Random Variables. Yesterday we calculated the mean number of goals for a randomly selected team in a randomly selected game.
5.8 Stem-and-Leaf Plots Standards: SDP 1.1, SDP 1.3 Objective: Use stem-and-leaf plots and back-to-back stem-and-leaf plots.
Objective: Learn to describe the relationships and extend the terms in arithmetic sequence.
MODALITIES OF STUDENT PARTICIPATION IN THE ORGANS AT THE UNIVERSITY OF MARIBOR, SLOVENIA.
Objective: To find the opposite and the absolute value of an integer.
Section 1.1, Slide 1 Copyright © 2014, 2010, 2007 Pearson Education, Inc. Section 11.3, Slide 1 11 Voting Using Mathematics to Make Choices.
Chapter 11. Weighted Voting Systems  Goals Study weighted voting systems ○ Coalitions ○ Dummies and dictators ○ Veto power Study the Banzhaf power index.
Weighted Voting Systems Chapter 2 Objective: Calculate the Banzhaf power Index for a weighted voting system. Learn additional notation and terminology.
Weighted Voting Systems Chapter 2 Objective: Recognize the notation for weighted voting system and be able to define quota, player, dictator, dummy and.
LESSON 19: UNDERSTANDING VARIABILITY IN ESTIMATES Student Outcomes Students understand the term sampling variability in the context of estimating a population.
EXCURSIONS IN MODERN MATHEMATICS SIXTH EDITION Peter Tannenbaum 1.
The Banzhaf Power Index
Excursions in Modern Mathematics Sixth Edition
Chapter 11: Weighted Voting Systems Lesson Plan
Excursions in Modern Mathematics Sixth Edition
Warm Up – 5/27 - Monday How many people voted in the election?
Linear Models and Equations
Chapter 11: Weighted Voting Systems
Choose the best answer for each problem.
Arithmetic Sequence Objective:
How many connecting cubes do you need to create this model?
Geometric Mean.
Solving Equations involving Decimal Coefficients
Weighted Voting.
Chapter 11: Weighted Voting Systems Lesson Plan
Proportional Representation
The Banzhaf Power Index
Discrete Math Weighted Voting.
EXAMPLE 4 Solve proportions Solve the proportion. ALGEBRA a x 16
Presentation transcript:

Weighted Voting Problems

Problem 1 1. The disciplinary board at PU is composed of 5 members, two of whom must be faculty and three of whom must be students. To pass a motion requires at least 3 votes and at least one of these must be from a faculty member. a. Find the Banzhaf power distribution of the disciplinary board. b. Describe the board as a weighted voting system [q:f,f,s,s,s].

Problem 2 2. a. Consider the weighted voting system [22:10,10,10,10,1]. Are there any dummies? Explain. b. Using your answer from part a. find the Banzhaf power distribution of this weighted voting system. (You shouldn’t have to do any work except a little arithmetic!) c. Consider the weighted voting system [q:10,10,10,10,1]. Find all the possible values of q for which the fifth participant is not a dummy. d. Consider the weighted voting system [34:10,10,10,10,w]. Find all positive integers w where the last participant is a dummy.

Problem 3 3. Consider the weighted voting systems [9:w,5,2,1]. a. What are the possible values of w? b. Which values of w result in a dictator? Who is it and why are they a dictator? c. Which values of w result in a participant who has veto power? Who is it? d. Which values of w result in one or more dummies?

Problem 4 4. a. Verify that the weighted voting systems [12:7,4,3,2] and [24:14,8,6,4] result in the same Banzhaf power distribution. (Do the calculations side by side and look for patterns.) b. Based on your work in part a. explain why two proportional weighted voting systems [q:w1,w2,...,wN] and [cq:cw1,cw2,...,cwN] always have the same Banzhaf power distribution.

Problem 5 5. Consider the weighted voting system [q:5,4,3,2,1]. a. For what values of q is there a dummy? b. For what values of q do all players have the same power?