Course: Introduction to Political Science (POLS 1) · Silver Oak University (fictional sample) · Prof. Halloran
Module: Week 12 of 16 · Fall 2026 · in-person, two 75-minute sessions
Objectives covered: Objective 6 — explain public opinion, polling, political behavior, and the media's role, as part of American government and political participation.

This file holds two pieces: (A) the Module 12 Overview page ("Start Here") and (B) the Welcome Announcement that drips out when the module opens. Week 12 runs Mon Nov 16 – Sun Nov 22, meeting Tue Nov 17 and Thu Nov 19, with end-of-week work due Sunday Nov 22, 11:59 p.m. (initial discussion post Fri Nov 20). Adjust the day-of-week and times to match your section.

(A) Module 12 Overview — Start Here

Welcome to Week 12: Public Opinion, Political Behavior & the Media

This is your home base for the week. Read it first, then work the checklist below from top to bottom. Everything you need is linked inside the module.

Every week, pollsters tell you "62% of Americans think…" and news feeds decide what you see. This week you learn how that number gets made — and how much to trust it. We cover how public opinion is measured (random sampling and the margin of error), what shapes people's political views in the first place (political socialization), who actually shows up to participate, and how the media shapes what we think is important (agenda-setting, framing) — a research finding presented with its critics, the way the field actually treats it. This is the course's second quantitative pocket: real math, kept small, always shown its work.

The week's big question

"How do we know what 'the public' thinks — and how much should a leader's own judgment weigh against it?"

By Sunday you'll be able to compute a poll's margin of error from its sample size, explain why a bigger sample can't fix a biased one, and take a real, current national poll apart the way a political scientist does — sample, field dates, margin of error and all.

By the end of this week, you can…

Use this as a checklist. If you can do all four out loud, you're ready for the quiz.

• [ ] Explain why random sampling works — and compute a poll's margin of error from its sample size (MoE ≈ 1.96 × √(0.25/n) at 95% confidence).
• [ ] Distinguish margin of error from bias — and explain why a larger sample size cannot fix a biased (non-random) sample.
• [ ] Describe political socialization and turnout patterns — what shapes political views, and who tends to participate.
• [ ] Read a real Pew Research Center poll release — sample, field dates, topline figures, and stated margin of error — the way a political scientist does, and sort media-effects findings from the media-effects critiques.

What's due this week, and when

Work these in order — each one gets you ready for the next.

Heads-up on the AI tools: you'll use a chatbot to draft and explain, and then you judge its work against the real poll and the record. Chatbots routinely invent poll numbers, blur margin of error with bias, and slide from correlation to causation. Catching the model is the point — in the tutorial, the assignment, and the workshop.

Late policy reminder: 10% off per day late. If life happens, reach out before the deadline — I'd much rather hear from you early.

How to succeed this week

• Lead with the question, not the formula. "How do we know?" comes before any number. A poll of 1,000 people can tell you about 200 million people only because it was sampled randomly — that's the whole trick, and it's worth understanding before you touch the arithmetic.
• Memorize one tiny hook. "Bigger fixes precision, not bias." A huge biased sample is still biased; a modest random sample is trustworthy within its stated margin. Ask this of every poll you meet this term (and after).
• Read the release like a source, not a headline. Who was sampled? When? How many? What's the stated margin of error? A headline number without those four facts isn't yet data you can use.
• Treat the chatbot as a confident intern, not an oracle. It will hand you a poll "statistic" that sounds exactly right and doesn't appear anywhere in the actual release — this week you'll catch it doing that with a real, current Pew report. Your job all term is to check it against the source.
• Expect fairness, practice fairness. This course never tells you which ideology or party is right, and it never both-sides a documented number. When we hit the delegate-vs-trustee question — this week's discussion — you'll get the strongest case for each side, and you'll be asked to state the side you disagree with fairly before you argue.

You don't need any background for this week beyond Week 1's toolkit and Week 11's first taste of political data. Come to class ready to defend a real answer to "should politicians follow the polls?" See you Tuesday.

(B) Welcome Announcement — Module 12

Release setting: post on the module's start day (offset = 0 days), i.e., Mon Nov 16, 2026 — not before. If your platform won't preserve the scheduled date on import, post this as a draft labeled "Release: Mon Nov 16."

Subject: Welcome to Week 12 — what do "62% of Americans" actually mean? 📊

Hi everyone, and welcome to Week 12!

Quick warm-up: the next time you see a headline that says "X% of Americans believe Y," stop for one second and ask four questions — who was asked, how many, when, and what's the margin of error? Almost nobody asks. This week, you will.

This week — Public Opinion, Political Behavior & the Media — we tackle the big question: How do we know what "the public" thinks — and how much should a leader's own judgment weigh against it? You'll learn why random sampling lets a poll of a couple thousand people describe a nation of hundreds of millions, how to compute a poll's margin of error, why a bigger sample can't rescue a biased one, and how political scientists study what shapes people's views and who shows up to participate. We'll also look honestly at the media's role — agenda-setting and framing are real, well-documented research findings, and so are the critiques of how far they reach.

Three things not to miss:
1. Lecture Tutorial 12 — work through the week's ideas with one approved chatbot (Gemini, Claude, or ChatGPT) and submit the share link. You'll catch the model's mistakes, not just trust it. Due Sun Nov 22.
2. Political Analysis Workshop 12 — a real, current Pew Research Center poll release — this week's workshop uses an actual national survey, published just weeks before this term, with every number verified against Pew's own methodology page. Quiz 12, Discussion 12, and Assignment 12 also close Sun Nov 22 — the workshop is the heart of the course, so start early.
3. Open the Start Here page first — it lays out everything in order with due dates.

One promise, right up front: this week hands you real numbers from a real, current national poll — and it will never tell you what conclusion to draw from them. You'll learn to read the data plainly (what it shows) and to keep that separate from the normative debate built on top of it (what leaders should do about it). Your grade never depends on which side you take — only on your evidence and reasoning.

Bring your curiosity (and healthy skepticism about the next poll number you see) to class on Tuesday.

See you soon,
Prof. Halloran