Learn statistics, one story at a time.

Joined July 2021
15 Photos and videos
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How do you pick the perfect sample? In @TheStatsStory's article, discover essential sampling methods like Stratified Random Sampling and Cluster Sampling, exploring how they address challenges in heterogeneous populations. towardsdatascience.com/stati…

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In statistics, sampling is more than just picking a few items, it's about ensuring those items represent the whole. From Convenience Sampling to Cluster Sampling, discover how different techniques can impact the quality of your research in this article by @TheStatsStory. towardsdatascience.com/stati…

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What is the Cramér–Rao Bound, and how is the Cramér–Rao Bound applied to regression models? 🤔 Explore more in @TheStatsStory's article now! #Statistics #Variance towardsdatascience.com/the-c…

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Ready to understand Fisher Information from the ground up? @TheStatsStory dismantles and rebuilds the formula step-by-step, uncovering the insights behind it. #Statistics towardsdatascience.com/fishe…

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.@TheStatsStory explores the Cramér–Rao Bound. From understanding its variance and precision forms to applying it in regression modeling with real datasets, unpack it all in this article. #Statistics #Variance towardsdatascience.com/the-c…

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Join @TheStatsStory as he explores Fisher Information! He’ll tackle what it means, why the formula looks the way it does, and how to calculate it for various distributions. #Statistics towardsdatascience.com/fishe…

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What does the “Information” in Fisher Information really mean? Join @TheStatsStory as he unpacks this key concept, connecting it to the precision of regression models. Read now! #Statistics towardsdatascience.com/fishe…

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For a comprehensive, accessible introduction to the omitted-variable bias — from its potential effects to its mathematical representation — don't miss @TheStatsStory's recent deep dive. towardsdatascience.com/omitt…

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In this article, Sachin Date (@TheStatsStory) examines a specific class of errors. The kind that cause your model’s predictions to consistently veer off in a particular direction regardless of the input. #DataScience #Regression #RegressionModel towardsdatascience.com/how-b…

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A deep dive into the causes, effects, and remedies for bias in regression models by Sachin Date (@TheStatsStory) towardsdatascience.com/how-b… #Regression #RegressionModel #DataScience

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Looking for an engaging and enlightening read at the intersection of data science, statistics, history, and political analysis? Don't miss @TheStatsStory's latest deep dive, which tells the story of the 1936 U.S. presidential election (and how a famous straw poll got it wrong). buff.ly/3MnRPLK

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An intro to a statistical bias that makes its brutal presence felt through a complete absence of data towardsdatascience.com/nonre…

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"A tsunami of scholarly analysis attempting to explain the Digest’s polling blunder followed the election." @TheStatsStory looks at the polling errors around the 1936 U.S. election, and uses them as the starting point for a comprehensive explainer on the non-response bias and the complexities of sampling. buff.ly/3MnRPLK

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Gain a deeper, intuitive understanding of conditional probability (and how it fits within Bayes' theorem) by following along @TheStatsStory's accessible primer, which demonstrates how this concept "underpins the design of every single regression model." buff.ly/3ScgLca

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For a comprehensive, accessible introduction to the omitted-variable bias — from its potential effects to its mathematical representation — don't miss @TheStatsStory's latest deep dive. buff.ly/3WTzU5C

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