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Course

Case Studies in Statistical Thinking

Intermediate

4.9+

Updated 05/2025

Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.

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PythonProbability & Statistics4 hours16 videos61 Exercises4,850 XP15,444Statement of Accomplishment

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Course Description

Mastery requires practice. Having completed Statistical Thinking I and II, you developed your probabilistic mindset and the hacker stats skills to extract actionable insights from your data. Your foundation is in place, and now it is time practice your craft.In this course, you will apply your statistical thinking skills, exploratory data analysis, parameter estimation, and hypothesis testing, to two new real-world data sets. First, you will explore data from the 2013 and 2015 FINA World Aquatics Championships, where you will quantify the relative speeds and variability among swimmers. You will then perform a statistical analysis to assess the "current controversy" of the 2013 Worlds in which swimmers claimed that a slight current in the pool was affecting result. Second, you will study the frequency and magnitudes of earthquakes around the world. Finally, you will analyze the changes in seismicity in the US state of Oklahoma after the practice of high pressure waste water injection at oil extraction sites became commonplace in the last decade. As you work with these data sets, you will take vital steps toward mastery as you cement your existing knowledge and broaden your abilities to use statistics and Python to make sense of your data.

Prerequisites

Statistical Thinking in Python (Part 1)Statistical Thinking in Python (Part 2)

1

Fish sleep and bacteria growth: A review of Statistical Thinking I and II

Activity of zebrafish and melatonin

EDA: Plot ECDFs of active bout length

Interpreting ECDFs and the story

Bootstrap confidence intervals

Parameter estimation: active bout length

Permutation and bootstrap hypothesis tests

Permutation test: wild type versus heterozygote

Bootstrap hypothesis test

Linear regressions and pairs bootstrap

Assessing the growth rate

Plotting the growth curve

2

Analysis of results of the 2015 FINA World Swimming Championships

Introduction to swimming data

Graphical EDA of men's 200 free heats

200 m free time with confidence interval

Do swimmers go faster in the finals?

EDA: finals versus semifinals

Parameter estimates of difference between finals and semifinals

How to do the permutation test

Generating permutation samples

Hypothesis test: Do women swim the same way in semis and finals?

How does the performance of swimmers decline over long events?

EDA: Plot all your data

Linear regression of average split time

Hypothesis test: are they slowing down?

3

The "Current Controversy" of the 2013 World Championships

Introduction to the current controversy

A metric for improvement

ECDF of improvement from low to high lanes

Estimation of mean improvement

How should we test the hypothesis?

Hypothesis test: Does lane assignment affect performance?

Did the 2015 event have this problem?

The zigzag effect

Which splits should we consider?

EDA: mean differences between odd and even splits

How does the current effect depend on lane position?

Hypothesis test: can this be by chance?

Recap of swimming analysis

4

Statistical seismology and the Parkfield region

Introduction to statistical seismology and the Parkfield experiment

Parkfield earthquake magnitudes

Computing the b-value

The b-value for Parkfield

Timing of major earthquakes and the Parkfield sequence

Interearthquake time estimates for Parkfield

When will the next big Parkfield quake be?

How are the Parkfield interearthquake times distributed?

Computing the value of a formal ECDF

Computing the K-S statistic

Drawing K-S replicates

The K-S test for Exponentiality

5

Earthquakes and oil mining in Oklahoma

Variations in earthquake frequency and seismicity

EDA: Plotting earthquakes over time

Estimates of the mean interearthquake times

Hypothesis test: did earthquake frequency change?

How to display your analysis

Earthquake magnitudes in Oklahoma

EDA: Comparing magnitudes before and after 2010

Quantification of the b-values

How should we do a hypothesis test on differences of the b-value?

Hypothesis test: are the b-values different?

What can you conclude from this analysis?

Closing comments

Case Studies in Statistical Thinking

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