This is a detailed learning plan for a high schooler (sophomore and above) during an 8-week period. Students are expected to have basic knowledge about programming and statistics. The workload is 2-3 hours per day during the weekday.

Learning objective

To develop essential skills for data analysis, including visualization, summarization, basic statistical inference, and generating report.

Content

Basic statistics knowledge

• Understand data format: vector and matrix
• Understand concept of data distribution.
• Summary statistics: mean, meian, variance, standard deviation, proportions.
• Understand concept of data visualization and their relationship with data distribution and summary statistics: boxplot, histogram, scatter plot, bar plot.
• Concept of correlation and contingency table.
• Basic statistical inference: two group t- and z-test, simple linear regression.

Programming language

• R: for data analyses and visualization
  • Basic usage of Rstudio
  • Using R console for basic numeric computation.
  • Understand R data types including vectors, matrix, data frame
  • File input and output: how to read in files and write results out.
  • Basic R graphics, and how to output R figures to file.
  • Basic data analyses: compute summary statistics, simple statistical test, linear regression.
• markdown and Rmarkdown: for writing reports.
  • Create markdown files, convert to pdf and/or html.
  • Basic commands for different type of format
  • How to include figures in the document
  • How to include Latex style equations
• A littlt bit of Latex.
  • I don’t expect students to write standalone latex document, but they need to know how to use latex to write equations, and insert those in Rmarkdown documents.

Data analysis

• Analyze a dataset for COVID-19.
• Write a final report in the standard format of a scientific paper.

Materials

Below are some selected materials, websites, and videos. I’ll also use other materials, detailed in the weekly schedules.

• R
  • R Tutorial for Beginners
  • R Basics: Quick and Easy
  • Youtube: introduction to rstudio for beginners
  • Youtube: Getting started with R and RStudio
• markdown
  • Markdown guide
  • Markdown tutorial
  • Youtube: An introduction to markdown
• Latex
  • Latex math and equations
• Rmarkdown
  • R Markdown Quick Tour
  • R Markdown tutorial

Weekly schedules

Click the link for each week for detailed learning schedule and homework. All homework need to be written in R, markdown, or Rmarkdown.

• Week 1:
  • Install R and R studio.
  • Understand R and R studio basics.
  • Understand basic R data type and operator: scalar, vector, matrix. Understand how to combine and subset vector and matrix.
  • Install a Markdown editor. Write a simple markdown document.
• Week 2
  • Understand the concept of R packages. Learn to install packages.
  • R data frame and list.
  • R file I/O (input/output): Understand tab-delimited and csv files. How to read those files into R, and write the results out to a text file.
    
  • How to save and load R objects.
  • Statistics:
    • understand mean, median, variance, standard deviation, etc. Learn to use R to compute these values.
    • understand the concept of continuous and categorical data, and their data distribution. understand the meaning of histogram, boxplot, barplot.
  • Basic R graphics. Understand the meaning of different type of plots. Use R to generate the plots.
  • Learn to save the figures from R session to pdf/jpg/png/etc.
  • Markdown: play with different type of fonts, ordered and unordered list, including figures. Write a complete markdown document.
• Week 3
  • R programming control statement: loops, if-else.
  • R graphics: plot with the color, line types, point types, legend, etc.
  • Basic Latex.
  • R markdown.
• Week 4
  • Random number generator in R.
  • More advanced R graphics:
    • overlay lines on scatterplot.
    • Multiple panels in one figure.
    • Colors in R.
    • Figure margins.
  • Basic statistics:
    • Concept of random variable and probability distribution.
  • Learn Latex math symbols. Insert latex equations in Rmarkdown.
• Week 5
  • Concept of corrleation, contingency table. Relationships among more than one variables (continuous and/or categorical).
  • Use scatterplot and boxplot to explore relationships among more than one variables.
  • Understand the concept of simple linear regression.
  • Use R to do linear regression.
  • Write R function.
• Week 6
  • Linux system and commands.
  • R graphics, including base and ggplot2.
• Week 7
  • R animation
  • Review some earlier contents.
• Week 8
  • Write a review for the whole course.
  • COVID-19 data anaysis. Write a report.