Significance

To P, or Not to P, That is the Question | Stats + Stories Episode 194 by Stats Stories

For years now, the utility of the P-value in scientific and statistical research has been under scrutiny – the debate shaped by concerns about the seeming over-reliance on p-values to decide what’s worth publishing or what’s worth pursuing. In 2016 the American Statistical Association released a statement on P-values, meant to remind readers that, “The P-values was never intended to be a substitute for scientific reasoning.” The statement also laid out six principles for how to approach P-values thoughtfully. The impact of that statement is the focus of this episode of Stats and Stories with guest Robert Matthews.

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Understanding What Causes Data Bias | Stats + Stories Episode 188 by Stats Stories

Dr. Charna Parkey is a lead data scientist at Kaskada, where she works on the team to deliver a commercially available data platform for machine learning. Her interests include analysis of different language patterns as well as using data science to combat systemic oppression. She has over 15 years’ experience in enterprise data science and adaptive algorithms in the defense and startup tech sectors and has worked with dozens of Fortune 500 companies in her work as a data scientist.

Episode Description

Our modern understanding of big data and the increasingly sophisticated tools we have for analyzing them have opened up whole new worlds for exploration. And, sometimes, whole new avenues for the misuse of data, which has led some to wonder who should be responsible or held accountable for data misuse or data bias? That’s the focus of this episode of Stats and Stories with Charna Parkey.

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19th Century Data Visualization | Stats + Stories Episode 154 by Stats Stories

Data visualization is a skill that's becoming increasingly important. In feels as wide-ranging as Education, Medicine and Journalism. It's also something that can seem incredibly complicated and imitating. The Fear Factor around creating visualization can obscure the long history of their use. People like W.E.B. DuBois and Florence Nightingale created data visualizations that don't different from what we might see today. The arguments made by such visualisations is a focus of this episode of Stats and Stories where we explore the statistics behind the stories with guest Alison Hedley.

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Analyzing Art Through Text Mining | Stats + Stories Episode 79 by Stats Stories

Julia Silge is a data scientist at Stack Overflow, with a PhD in astrophysics and an abiding love for Jane Austen. She is both an international speaker and a real-world practitioner focusing on data analysis and machine learning practice. She is the author of Text Mining with R, with her coauthor David Robinson. She loves making beautiful charts and communicating about technical topics with diverse audiences.

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