– wrangling data in an efficient and reproducible way
– regression analysis and hypothesis testing
– using tidyverse for data analysis
– improve data visualization skills
Announcements
We have an exam soon (Feb-20th)
Exam-1 is worth 20% of your grade, split equally between
– In-class exam
– Take-home exam
In-class exam
– Closed computer
– Bring handwritten 8x11 sheet of paper (front and back)
Types of questions
– Multiple choice; True False; Short answer; Fill in the blank
– Plot critiques
– What would code produce
Questions?
Take-home exam
– Think about this as a more involved homework
– Questions geared towards applying what we have learned
– Extension question that pushes you to explore something new
Questions?
Homework-2
library(palmerpenguins)mean_bill <- penguins |>summarise(mean_bl =mean(bill_length_mm))mean_bill # this is unnecessary
Homework-2
penguins |># short comments to explain code are very helpfulsummarise(mean_bl =mean(bill_length_mm, na.rm = T)) # and a very good habit# but we want to make sure that we don't put a large amount of text as a comment. The nice thing about Quarto is that is renders together text, code, and output. Any text that isn't a helpful quick code comment should go outside of our code chunk
Warm-up
What are Wide data? What are Long data?
Warm-up
What are Wide data? What are Long data?
– Wide data contains values that do not repeat in the first column
– Long data contains values that do repeat in the first column
pivot_wider
pivot_wider
– Making tables for quick comparison / display purposes
