# Summer 1 2010 - 94225 - PA325 - Topics in Policy

### Quantitative Foundation in Public Policy

Instructor(s): |
Spelman, William |

Unique Number: |
94225 |

Day & Time: |
MTW 6:00 - 8:30 pm |

Room: |
SRH 3.122 |

Waitlist Information: | For LBJ Students: UT Waitlist Information |

##### Course Overview

These undergraduate elective seminars cover a wide range of public affairs issues. Among recent topics are ethical leadership, modern American social policy, and philanthropy.

##### Section Description

In theory, public policy is easy enough that George Will and Frank Rich can explain it all for you in the newspaper. In reality, it’s hard enough that Jon Stewart and Steve Colbert will never run out of material. The difference between simple theory and stupid government action is often the failure to answer questions like, “How much?” This course is designed to give participants the mathematical background they need to make sense of them and to begin to resolve them. We’ll cover four, basic issues:

**Functions and graphs** - Policy analysts need to visualize and graph relationships among variables, describe them precisely in words, and manipulate the *xs and ys*. They also need to be able to use transcendental functions – e and logarithms – and solve simultaneous algebraic equations.

**Differential calculus** – If *w* depends on *x, y, *and *z*, how much will *w* change if we change each of the others just a little bit? That’s what calculus is for. After considering the basic rules of differentiation, we’ll apply them to some optimization problems: What should we set x, y, and z to, if we want the highest or lowest amount of *y*?

**Probability** – Much of what we need to know is expressed in terms of probabilities. We’ll consider the multiple meanings of probability, calculate probabilities from raw data, and make logical connections among probability statements. Along the way, we’ll also demonstrate why none of us knows as much as we think we do, and what we can do to adjust for that.

**Statistics** – Analysts often use graphs and statistical measures to summarize the shape of a batch of numbers or *distribution*. We’ll also examine some public policy applications of the binomial and normal probability distributions, and consider the meaning and construction of confidence intervals.

At the end, you won’t be able to go toe-to-toe with Paul Krugman (an excellent urban economist before *he* became a rich and famous pundit). But you will have the background to take on graduate work in public policy.

This course serves as the foundation to quantitative analysis in the graduate policy curriculum in general, and as the prerequisite to the quantitative sequence in the M.P.Aff. program at the LBJ School in particular. No prior knowledge of calculus or statistics is required, but students enrolling in this course are expected to have a background in basic algebra. It’s OK if you’re a little rusty. You were probably better prepared for this class when you were 15, but it will all come back when you need it.