Science Research Weekly

Episode 9: Boxes and Babies

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In this episode I thought outside the Box-Pierce; fuzzed, sweated, and flustered my way through basic stats; encountered functions and AI for babies; and chronicled the R-package ‘chronicler’.

References:

  • NeuralSens: Sensitivity Analysis of Neural Networks
  • econet: An R Package for Parameter-Dependent Network Centrality Measures
  • Modified Quantile Regression For Modeling the Low Birth Rate
  • A Novel Correction for the Adjusted Box-Pierce Test
  • Comments on identifying causal relationships in nonlinear dynamical systems via empirical mode decomposition
  • Adaptive numerical simulations with Trixi.jl: A case study of Julia for scientific computing
  • The balanced bootstrap in SAS
  • Game-changer AI tool will save mothers and babies
  • D. Mayo & D. Hand: “Statistical significance and its critics: practicing damaging science, or damaging scientific practice?”
  • Fuzzy Clustering: Definition
  • How to Find the P value: Process and Calculations
  • The Difference Between an Odds Ratio and a Predicted Odds
  • ‘Data analysis with tidyverse’ workshop
  • Think like a programmeR: the workshop
  • How to add labels at the end of each line in ggplot2?
  • Subsetting with multiple conditions in R
  • Hierarchical data visualization with Shiny and D3
  • chronicler: Add Logging to Functions

    • R-packages:

    • Rwclust: Random Walk Clustering on Weighted Graphs
    • ScaleSpikeSlab: Scalable Spike-and-Slab
    • webshot2: Take Screenshots of Web Pages
    • mverse: Tidy Multiverse Analysis Made Simple
    • chronicler: Adding Logging to Functions
      • ...more
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      Science Research WeeklyBy Mark R Williamson