Rephonic
Artwork for Casual Inference
Causal Inference
Public Health
Biostatistics
Statistics
Epidemiology
Directed Acyclic Graphs
Game Theoretic Statistics
Large Language Models
Econometrics
Data Cleaning
Machine Learning
Public Policy
Data Science
Immortal Time Bias
Clone Sensor Weight Method
Sequential Anytime Valid Inference
Treatment Heterogeneity
Generalizability
Disney
Mediation Analysis

Keep it casual with the Casual Inference podcast. Your hosts Lucy D'Agostino McGowan and Ellie Murray talk all things epidemiology, statistics, data science, causal inference, and public health. Sponsored by the American Journal of Epidemiology.

PublishesWeeklyEpisodes76Founded7 years ago
Number of ListenersCategories
MathematicsScience

Listen to this Podcast

Artwork for Casual Inference

Latest Episodes

Follow Regression to the Mean Girls on [⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠], [⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠], or wherever you love to listen!

Hannah Barton joins ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Sarah Lotspeich⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Lucy D'Agostino McGowan⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ with a data-driven s... more

Follow Regression to the Mean Girls on [⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠], [⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠], or wherever you love to listen!

Roger Peng⁠ joins ⁠⁠⁠⁠⁠⁠⁠⁠⁠Sarah Lotspeich⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠Lucy D'Agostino McGowan⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ with a data-driven side quest ... more

Follow Regression to the Mean Girls on [⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠], [⁠⁠⁠⁠Spotify⁠⁠⁠⁠], or wherever you love to listen!

Mattan Ben-Shachar⁠ joins ⁠⁠⁠⁠⁠⁠⁠⁠Sarah Lotspeich⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠Lucy D'Agostino McGowan⁠⁠⁠⁠⁠⁠⁠⁠⁠ with a data-driven side quest ... more

Follow Regression to the Mean Girls on [⁠⁠⁠Apple Podcasts⁠⁠⁠], [⁠⁠⁠Spotify⁠⁠⁠], or wherever you love to listen!

⁠Emily Riederer⁠⁠⁠⁠⁠ (Capital One) joins ⁠⁠⁠⁠⁠⁠⁠Sarah Lotspeich⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠Lucy D'Agostino McGowan⁠⁠⁠⁠⁠⁠⁠⁠ with a data-driven side... more

Key Facts

Accepts Guests
Contact Information
Podcast Host
Number of Listeners
Find out how many people listen to this podcast per episode and each month.

Similar Podcasts

People also subscribe to these shows.

SERious EPI
SERious EPISue Bevan - Society for Epidemiologic Research
The Daily
The DailyThe New York Times

Recent Guests

Hannah Barton
PhD student in Speech and Hearing Sciences researching language development and neurodevelopmental disabilities
University of Washington
Episode: Regression to the Mean Girls | Mixed Effects, Mixed Signals: Love Island Kissing Scores with Hannah Barton
Roger Peng
Professor of Statistics and Data Sciences at the University of Texas at Austin and data science and statistics author
University of Texas at Austin
Episode: Regression to the Mean Girls | Every Man's Causal Inference with Roger Peng
Mattan Ben-Shachar
Freelance research analyst and statistical consultant specializing in the social sciences
Independent / EasyStats project contributor
Episode: Regression to the Mean Girls | The Marshmallow Test (Not That One) with Mattan Ben-Shachar
Emily Riederer
Data scientist at Capital One
Capital One
Episode: Regression to the Mean Girls | Election Data Web Scraping with Emily Riederer
Hadley Wickham
Chief Scientist at Posit, leads the Tidyverse team
Posit
Episode: Regression to the Mean Girls | The Art of Web Scraping Art with Hadley Wickham
Christine Zhang
New York Times reporter specializing in graphics and data journalism
New York Times
Episode: Regression to the Mean Girls | The Comfort of Competence and the Speed of Justice, According to Law & Order
Sarah Lotspeich
Presenter and data storyteller for this episode
Episode: Regression to the Mean Girls | Romance by the Numbers: First Sparks Across Tropes
Carly Brantner
Assistant Professor of Biostatistics and Bioinformatics at Duke University and the Duke Clinical Research Institute.
Duke University
Episode: Combining Data & Making Effects Generalizable with Carly Brantner | Season 6 Episode 7
Andrew Heiss
Assistant Professor in the Department of Public Management and Policy
Georgia State University
Episode: The Art of Clarity with Andrew Heiss | Season 6 Episode 6

Hosts

Lucy D'Agostino McGowan
Co-host of the show and researcher with a strong background in epidemiology and data science.
Ellie Murray
Co-host and independent epidemiologist deeply engaged in making complex statistical concepts approachable.

Reviews

4.6 out of 5 stars from 241 ratings
  • Best causal inference podcast

    My only wish is for more input from sciences outside biology and from the computer science side of causal inference research. A lot is being done well and a lot is being done poorly in ML and causal ML. I’d love to hear more on this.

    Apple Podcasts
    4
    Complemental
    United Statesa year ago
  • Great content

    I absolutely love the content of this podcast. Everything about it. I just listened to the optimizing data workflows episode and the tone and use of filler language were out-of-control distracting. It was hard to get through and focus on what was being said, which is was very interested in. If the hosts can work on minimizing the, “like, literally, whatever” 💁🏻‍♀️, then this would be a perfect podcast.

    Apple Podcasts
    4
    Megjhart
    United Statesa year ago
  • hello, there are people listening to you

    My first encounter with this podcast, an episode about subject X. The hosts start by discussing the topic of the previous episode and keep taking about it. I skip a few minutes and start from 9 minutes into the episode. They still have not moved to subject X! It’s nice that they’re enjoying the conversation and have an opportunity to think deeply about that previous issue, but what about the audience?

    Apple Podcasts
    2
    Baal'sack
    United Kingdoma year ago
  • Guests don’t get to talk much

    They invite amazing guests, but it’s mostly the hosts who do most of the talking. Please let your guests talk!

    Apple Podcasts
    2
    Jminator001
    Canadaa year ago
  • Casual voices = casual infer!

    Two things. First and most importantly, this is among the very best, most fun, most useful podcasts I’ve found. Thank you both for the time and work that you devote to sharing your (and others’) expertise in this awesome podcast. Second (from this Linklater-trained sometime-performer, now translational almost-PhD, modeling enthusiast, chronically under-slept parent, here): GUYS! Guys (or girls). Lay off the vocal critiques. Women scientists get disproportionately scrutinized for anything other t... more

    Apple Podcasts
    5
    kkflo00177
    United Statesa year ago

Listeners Say

Key themes from listener reviews, highlighting what works and what could be improved about the show.

Many reviews highlight the podcast's unique approach to discussing data science and public health issues in a casual tone.
A few criticisms focus on the hosts' speaking style, suggesting that some listeners find it distracting rather than engaging.
Listeners appreciate the knowledge and expertise of the hosts, particularly in making complex subjects engaging and accessible.

Chart Rankings

How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.

Talking Points

Recent interactions between the hosts and their guests.

Regression to the Mean Girls | Mixed Effects, Mixed Signals: Love Island Kissing Scores with Hannah Barton
Q: What do the variance components suggest about how participants score the kisses?
Partner variance accounts for about 20 to 30 percent and relationship variance about 70 to 75 percent, while actor variance is small. Most scores fall in a similar range, with occasional outliers reflecting social dynamics.
Regression to the Mean Girls | Mixed Effects, Mixed Signals: Love Island Kissing Scores with Hannah Barton
Q: How would you quantify the kissy-kisser interaction when you only have one measure per pair?
With only one score for each pairing, the relationship component cannot be separated from error, so they appear together as a combined variance component.
Regression to the Mean Girls | Every Man's Causal Inference with Roger Peng
Q: What do you think was the distribution of the sales price, like the final sales price for the book?
Peng says sales were concentrated at zero and at the suggested price, with only a few people paying slightly more; he estimates about 10% paid something.
Regression to the Mean Girls | Every Man's Causal Inference with Roger Peng
Q: What was your side quest and what data did you use, Roger?
Peng describes trying to become a businessman by selling data science books and experimenting with Twitter and Facebook ads, using the sales data from Leanpub and audience data from Google Analytics.
Regression to the Mean Girls | The Marshmallow Test (Not That One) with Mattan Ben-Shachar
Q: What were the key findings from the triangle test and the recognition task?
The triangle test showed a high posterior probability that people can correctly identify an odd marshmallow by color, with overall accuracy slightly above chance; the recognition task indicated discriminability is present but not definitive, suggesting flavor signals may be weak or confounded by color cues.

Audience Metrics

Listeners, social reach, demographics and more for this podcast.

Listeners per Episode
Gender Skew
Location
Interests
Professions
Age Range
Household Income
Social Media Reach

Frequently Asked Questions About Casual Inference

What is Casual Inference about and what kind of topics does it cover?

Focusing on topics related to epidemiology, statistics, data science, and causal inference, the conversations are both insightful and accessible, appealing to both laypeople and professionals. The hosts engage with experts across various fields, offering diverse perspectives on intricate subjects related to public health and data analysis. Unique for its casual tone, this podcast merges academic rigor with approachable dialogue, allowing listeners to grasp complex concepts without feeling overwhelmed.

Where can I find podcast stats for Casual Inference?

Rephonic provides a wide range of podcast stats for Casual Inference. We scanned the web and collated all of the information that we could find in our comprehensive podcast database. See how many people listen to Casual Inference and access YouTube viewership numbers, download stats, audience demographics, chart rankings, ratings, reviews and more.

How many listeners does Casual Inference get?

Rephonic provides a full set of podcast information for four million podcasts, including the number of listeners. View further listenership figures for Casual Inference, including podcast download numbers and subscriber numbers, so you can make better decisions about which podcasts to sponsor or be a guest on. You will need to upgrade your account to access this premium data.

What are the audience demographics for Casual Inference?

Rephonic provides comprehensive predictive audience data for Casual Inference, including gender skew, age, country, political leaning, income, professions, education level, and interests. You can access these listener demographics by upgrading your account.

How many subscribers and views does Casual Inference have?

To see how many followers or subscribers Casual Inference has on Spotify and other platforms such as Castbox and Podcast Addict, simply upgrade your account. You'll also find viewership figures for their YouTube channel if they have one.

Which podcasts are similar to Casual Inference?

These podcasts share a similar audience with Casual Inference:

1. The Indicator from Planet Money
2. Consider This from NPR
3. SERious EPI
4. Uncanny Valley | WIRED
5. The Daily

How many episodes of Casual Inference are there?

Casual Inference launched 7 years ago and published 76 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

How do I contact Casual Inference?

Our systems regularly scour the web to find email addresses and social media links for this podcast. We scanned the web and collated all of the contact information that we could find in our podcast database. But in the unlikely event that you can't find what you're looking for, our concierge service lets you request our research team to source better contacts for you.

Where can I see ratings and reviews for Casual Inference?

Rephonic pulls ratings and reviews for Casual Inference from multiple sources, including Spotify, Apple Podcasts, Castbox, and Podcast Addict.

View all the reviews in one place instead of visiting each platform individually and use this information to decide if a show is worth pitching or not.

How do I access podcast episode transcripts for Casual Inference?

Rephonic provides full transcripts for episodes of Casual Inference. Search within each transcript for your keywords, whether they be topics, brands or people, and figure out if it's worth pitching as a guest or sponsor. You can even set-up alerts to get notified when your keywords are mentioned.

What guests have appeared on Casual Inference?

Recent guests on Casual Inference include:

1. Hannah Barton
2. Roger Peng
3. Mattan Ben-Shachar
4. Emily Riederer
5. Hadley Wickham
6. Christine Zhang
7. Sarah Lotspeich
8. Carly Brantner

To view more recent guests and their details, simply upgrade your Rephonic account. You'll also get access to a typical guest profile to help you decide if the show is worth pitching.

Find and pitch the right podcasts

We help savvy brands, marketers and PR professionals to find the right podcasts for any topic or niche. Get the data and contacts you need to pitch podcasts at scale and turn listeners into customers.
Try it free for 7 days