Quant And Economics

Hypothesis And Regression Reading

Read test statistics, p-values, regression output, and model limitations without getting lost in tables.

Video Production Brief

This lesson is scripted for a rendered Remotion cut. The page below shows the voiceover and animation beats that should drive production.

Lesson Script

0:00-0:15

Hook

Visual

Open on the common miss pattern, then isolate the decision the candidate must make under time pressure.

Voiceover

If rejecting the null because the coefficient looks large, this topic starts to feel bigger than it is. We are going to make the decision visible.

0:15-0:40

Visual Model

Visual

A regression dashboard highlights coefficient, t-stat, p-value, R-squared, and residual pattern one at a time.

Voiceover

First, build the picture. The goal is to see the moving parts before trying to memorize the rule.

0:40-1:05

High-Yield Pass

Visual

Highlight the two highest-payoff ideas and remove the details that do not change the answer.

Voiceover

State the null and alternative before looking at the p-value Then Statistical significance is not economic significance

1:05-1:30

Trap Lab

Visual

Show two tempting answer paths, cross out the flawed one, and leave the reliable rule path on screen.

Voiceover

The tempting wrong answer usually comes from ignoring sign and units. We will name that trap before solving.

1:30-1:55

Repair Drill

Visual

End with one short drill prompt, a pause, and a clean reveal of the answer logic.

Voiceover

Your repair rep after this lesson is simple: read five regression outputs and identify the tested claim before calculating anything.

Lesson Objective

Help candidates interpret statistical output quickly and avoid overfitting their answer to one number.

Visual Teaching Plan

A regression dashboard highlights coefficient, t-stat, p-value, R-squared, and residual pattern one at a time.

High-Yield Map

  • State the null and alternative before looking at the p-value.
  • Statistical significance is not economic significance.
  • Regression output is a story about slope, fit, and reliability.

Common Traps

  • Rejecting the null because the coefficient looks large.
  • Ignoring sign and units.
  • Confusing correlation with causation.

Repair Drills

  • Read five regression outputs and identify the tested claim before calculating anything.
  • Write a one-sentence interpretation for each coefficient.