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Course

Case Studies in Statistical Thinking

IntermediateSkill Level

4.9+

Updated 09/2024

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 hr16 videos61 Exercises4,850 XP16,047Statement 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

To begin, you'll use two data sets from Caltech researchers to rehash the key points of Statistical Thinking I and II to prepare you for the following case studies!

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

In this chapter, you will practice your EDA, parameter estimation, and hypothesis testing skills on the 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

Some swimmers said that they felt it was easier to swim in one direction versus another in the 2013 World Championships. Some analysts have posited that there was a swirling current in the pool. In this chapter, you'll investigate this claim! References - Quartz Media, Washington Post, SwimSwam (and also here), and Cornett, et al.

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

Herein, you'll use your statistical thinking skills to study the frequency and magnitudes of earthquakes. Along the way, you'll learn some basic statistical seismology, including the Gutenberg-Richter law. This exercise exposes two key ideas about data science: 1) As a data scientist, you wander into all sorts of domain specific analyses, which is very exciting. You constantly get to learn. 2) You are sometimes faced with limited data, which is also the case for many of these earthquake studies. You can still make good progress!

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

Of course, earthquakes have a big impact on society, and recently are connected to human activity. In this final chapter, you'll investigate the effect that increased injection of saline wastewater due to oil mining in Oklahoma has had on the seismicity of the region.

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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FAQs

Is this course suitable for beginners?

Yes, this course is suitable for beginners who have already completed Statistical Thinking I and II. It will help to review the key points from these courses to prepare, but mastering the material in this course does not require advanced knowledge or skills.

Would I receive a certificate at the end of the course?

Yes, upon successful completion of the course and all associated tasks, you will receive a certificate to showcase your new skills.

What topics does this course cover?

This course covers topics such as exploratory data analysis, parameter estimation, and hypothesis testing. Additionally, it addresses the "current controversy" of the 2013 FINA World Swimming Championship, frequency and magnitudes of earthquakes, and changes in seismicity in the US state of Oklahoma due to high-pressure waste water injection.

What jobs would benefit from this course?

Employees who work in the fields of data science, statistical analysis, natural sciences, and seismology can all benefit from the knowledge gained in this course. Additionally, people wanting to pursue careers in these fields can gain important insights and skills.

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