03/01/2024

Slide 1: Introduction

  • Objective: Presenting a Statistical Modeling Shiny App.
  • Topics Covered: Data input, exploratory analysis, linear modeling.
  • Tools Used: Shiny, ggplot2.

Slide 2: Shiny App Structure

  • UI Definition:
    • Input data, data summary, model output, exploratory analysis.
  • Server Logic:
    • Reactive values, parsing input, updating plots, fitting linear model.

Slide 3: Input and Exploration

  • Data Input:
    • Comma-separated data entered via text input.
    • Button click triggers data analysis.
  • Exploratory Analysis:
    • Choose between Scatter Plot, Histogram, or Boxplot.

Slide 4: Model Fitting and Summary

  • Linear Model Fitting:
    • Simple linear regression model fitted to the data.
  • Model Summary:
    • Displayed on the app interface.
    • Includes coefficients, p-values, etc.

Slide 5: Descriptive Statistics

  • Descriptive Statistics:
    • Summary table presented in the main panel.
  • Conclusion:
    • Highlights of the Shiny app functionality.
    • Encourage further exploration.