Daily Schedule

To-Do
Download and Install R Link Video
Download and Install RStudio Link Video
Setup RStudio Video
Download packages File Video
Time Topic Links
09:00 - 09:30 Welcome Slides
09:35 - 10:30 Introduction to R and R Markdown Slides
10:45 - 12:00 Introduction to Data Slides ● File
Time Topic Links
09:00 - 09:50 Describing Data with Numbers Slides ● File
10:00 - 10:50 Interpeting Data Visualizations Slides
11:00 - 12:00 Visualizing Data Slides ● File
13:00 - 15:00 Lab: Summarizing Data File
Time Topic Links
09:00 - 09:40 Improving Data Visualizations Slides ● File
09:40 - 10:00 Pipe operator Slides
10:10 - 11:00 Subsetting and Grouping Data Slides ● File
11:10 - 12:00 Changing Variables Slides
Time Topic Links
09:00 - 09:30 R packages Slides ● File
09:30 - 10:00 Importing Data Slides
10:10 - 11:00 Data Joins Slides ● File
11:10 - 12:00 Review Slides ● File
13:00 - 15:00 Lab: Exploring Data Activity
Time Topic Links
09:00 - 09:50 Introduction to probability Slides ● Activity
10:00 - 10:50 Joint vs. marginal
11:00 - 12:00 Conditional probability and independence
Time Topic Links
09:00 - 09:50 Random variables Slides ● Activity
10:00 - 10:50 Probability distributions
11:00 - 12:00 Discrete vs. continuous distributions
Time Topic Links
09:00 - 10:20 Sampling distribution Slides ● File
10:30 - 12:00 Confidence interval Slides ● File ● File
Extra Overview Slides
Time Topic Links
09:00 - 09:50 Null vs. alternative Slides ● Activity
10:00 - 10:50 t-test
11:00 - 12:00 z-test for proportions
Time Topic Links
09:00 - 09:50 Two-sample t-test Slides ● Activity
10:00 - 10:50 Chi-squared test for contingency tables
11:00 - 12:00 Overview of the final project
Time Topic Links
09:00 - 09:50 Introduction Slides ● Activity
10:00 - 10:50 Binary explanatory variable
11:00 - 12:00 Numerical explanatory variable
Time Topic Links
09:00 - 09:50 Introduction Slides ● Activity
10:00 - 10:50 Additive models
11:00 - 12:00 Interaction
Time Topic Links
09:00 - 09:50 Introduction Slides ● Activity
10:00 - 10:50 One binary explanatory variable
11:00 - 12:00 Multiple explanatory variables

Review of statistical inference.

Data pre-processing and preliminary analysis for the final project.

Time Topic Links
09:00 - 09:30 Sample vs. Population Slides
09:30 - 10:00 Study Design Slides
10:10 - 11:00 Model Assumptions Slides
11:10 - 12:00 Model Evaluations Slides
Time Topic Links
09:00 - 10:00 Ethics Case Studies Link
10:10 - 11:20 Improving Data Visualizations Link
11:30 - 12:00 Studying Data Science in College Link
13:00 - 15:00 Model evaluation and validation for projects

Hands-on work on finalizing project analysis and communication of findings.

Time Topic Links
09:00 - 10:00 Practice within groups
10:10 - 12:00 Presentations and feedback
Time Topic Links
09:45 - 10:30 Final Presentations Slides