Summarize + Organize · Week 05
Descriptive Statistics + Data Frame
Interpret center and spread, practice vector selection, then learn how a data table becomes a data frame in R.
Sep 21–25Lecture 4 + Classwork 3Lecture 5
ImportantWeek 5 sequence
- Use Lecture 4 to complete descriptive statistics and vector selection.
- Use Classwork 3 to practice those ideas in R.
- Begin Lecture 5 by reading CSV files and getting to know a data frame.
Focus
- Center, spread, quartiles, IQR, and boxplots
- Vector selection
- CSV files, paths, and data-frame structure
Prepare
- Open Lecture 4 and Classwork 3
- Bring your R script and section project
- Open Lecture 5 when we begin working with data frames
Practice
- Calculate and interpret descriptive statistics
- Select vector values by position and condition
- Read and inspect a data frame
Learning targets
- Interpret measures of center and spread in context.
- Calculate and explain range, variance, standard deviation, quartiles, and IQR.
- Select vector values by position and logical condition.
- Read a CSV file into R as a data frame.
- Identify variables, observations, and values in a data frame.
Core pattern
data <- readr::read_csv("data/file.csv")
dplyr::glimpse(data)Lecture slides
TipLecture slide shortcuts
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