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Case Studies in Statistical Thinking

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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4 Hours16 Videos61 Exercises13,302 Learners4850 XP

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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.

  1. 1

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

    Free

    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!

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    Activity of zebrafish and melatonin
    50 xp
    EDA: Plot ECDFs of active bout length
    100 xp
    Interpreting ECDFs and the story
    50 xp
    Bootstrap confidence intervals
    50 xp
    Parameter estimation: active bout length
    100 xp
    Permutation and bootstrap hypothesis tests
    50 xp
    Permutation test: wild type versus heterozygote
    100 xp
    Bootstrap hypothesis test
    100 xp
    Linear regressions and pairs bootstrap
    50 xp
    Assessing the growth rate
    100 xp
    Plotting the growth curve
    100 xp
  2. 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!

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Datasets

Swimming results, 2013 World Aquatics ChampionshipsSwimming results, 2015 World Aquatics ChampionshipsZebrafish active bout lengthsOklahoma earthquakes (1950 to mid-2017)Bacterial growthParkfield earthquakes (1950 to mid-2017)

Collaborators

hugobowneHugo Bowne-AndersonyashasYashas Roy
Justin Bois Headshot

Justin Bois

Lecturer at the California Institute of Technology

Justin Bois is a Teaching Professor in the Division of Biology and Biological Engineering at the California Institute of Technology. He teaches nine different classes there, nearly all of which heavily feature Python. He is dedicated to empowering students in the biological sciences with quantitative tools, particularly data analysis skills. Beyond biologists, he is thrilled to develop courses for DataCamp, whose students are an excited bunch of burgeoning data scientists!
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Lloyds Banking Group

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Harvard Business School

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Decision Science Analytics, USAA

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