Week 9: Review Session

Week 9: Review Session#

STATS 60 Spring 2025

  • 10 bonus points for attendance

  • 10 bonus points for completing assignment

This week’s discussion section will be a review session for material you’ve learned this quarter so far.

Discussion assignment (extra credit, bonus points: 10):#

Come up with up to 3 questions you have about material we’ve covered in class so far, and enter them in the Google Poll by 07:00 AM on Thursday, May 29.

This is mostly to help you brainstorm. Your TA will answer a subset of the class’ questions in the discussion. If your question is not chosen, you’ll have time to ask it in section.

Discussion Agenda#

This week’s discussion will be a review session of the material in units 1-4, in order to help you start preparing for the final. TAs will answer questions about topics we have covered in class, including:

  1. Thinking about scale

    • Fermi problems

    • Cost-benefit analysis

  2. Probability

    • Simple experiments: sample spaces, outcomes, and events

    • Modeling uncertain situations with simple experiments

    • How to calculate probability of events

    • The law of the complement

    • Conditional probability

    • Bayes’ rule

    • Common mistakes and fallacies in conditional probability

    • Expectation

  3. Exploratory data analysis

    • Data visualization

    • Fundamental summary statistics:

      • mean

      • median

      • variance

      • standard deviation

      • quantiles

      • correlation and correlation coefficient

    • Mutli-modal data

    • Heavy-tailed and skewed data

    • Outliers

  4. Correlation and Experiments

    • The sample mean as an estimate

    • Sample size and the effect of sample size on standard deviation

    • Normal Approximation for the sample mean

      • Confidence intervals

      • 68-95-99 rule

    • Selection bias

    • Hypothesis testing

      • Null and alternative hypothesis

      • \(p\)-values

      • False positive and false negative rates

      • Level and statistical significance

      • multiple testing, family-wise error rate, Bonferroni correction

    • \(p\)-values for correlation coefficient from simulation

    • Experimental design

      • Randomized controlled trials vs. observational studies

    • Potential outcomes model

      • \(p\)-values from simulation

      • \(p\)-values from normal approximation

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