Patrick Curran

S3E23: The Mättrix Part II: Using Matrices To Our Advantage

In this week’s episode Greg and Patrick continue their discussion from last week in the Mättrix Part deux in which we continue to explore the magic of matrices including estimation, eigenvalues and eigenvectors. Along the way they  also discuss flawed audio transcripts, 50 shades of Greg, drunkenly shoving a matrix, drug mules, things you need, […]

S3E23: The Mättrix Part II: Using Matrices To Our Advantage Read More »

S3E21: A Low-Resolution Discussion of Sampling Distributions

In this week’s episode Greg and Patrick discuss the critical distinction between sample distributions and sampling distributions and we explore all the different ways in which sampling distributions are foundational to how we conduct research. Along the way they also discuss Starbucks jazz, one item tests, hot pockets, delusions of grandeur, Tetris and Pong, drawing

S3E21: A Low-Resolution Discussion of Sampling Distributions Read More »

S3E20: The Rise of Machine Learning in the Social Sciences with Doug Steinley

Patrick and Greg discuss the rise of machine learning in the social sciences with guest Doug Steinley who is a professor in the Department of Psychology at the University of Missouri at Columbia and is the current editor of the APA journal Psychological Methods. Along the way they also discuss funeral expenses, Swedish massage, Amy

S3E20: The Rise of Machine Learning in the Social Sciences with Doug Steinley Read More »

S3E19: Social Network Analysis: Making Connections with Tracy Sweet

In this week’s episode Greg and Patrick have a wonderfully engaging conversation with social network analysis expert Tracy Sweet who is an Associate Professor in the Department of Human Development and Quantitative Methodology at the University of Maryland. Tracy patiently helps us understand what social network analysis is, and how it can be used to

S3E19: Social Network Analysis: Making Connections with Tracy Sweet Read More »

S3E17: Logistic Regression: 2 Logit 2 Quit

Greg and Patrick explore the generalized linear model as a powerful framework for building regression models for binary and other discretely distributed dependent variables. Along the way they also discuss stealing property, statistical conspiracy theories, mic drops, coming uncorked, getting punched by biostatisticians, big logistic, tapping out, the Oakland Raiders, being 8.5 feet tall, sheep

S3E17: Logistic Regression: 2 Logit 2 Quit Read More »

S3E16: Your COVID Rapid Test Result: Are You Positive You’re Positive?

In today’s episode, Patrick and Greg use the context of COVID rapid tests to discuss issues of sensitivity, specificity, positive and negative predicted values, and the generally questionable utility of test accuracy information. Along the way they also discuss escape rooms, C4, Embassy Suites, palak paneer, 93% accurate, astragali, SAT prep courses, the volume of

S3E16: Your COVID Rapid Test Result: Are You Positive You’re Positive? Read More »

S3E15: Heywood You Help Me With Negative Residual Variances?

In today’s episode Greg & Patrick discuss the causes, consequences, and potential solutions associated with negative residual variances in factor analyses, a condition commonly called a Heywood case. Along the we way they also discuss vegetarian pepperoni, Jaws Part 2, coffin seat belts, balancing a ship, bad puns, sterilizing needles, dead canaries, hitchhikers, legal depositions,

S3E15: Heywood You Help Me With Negative Residual Variances? Read More »

Scroll to Top