ChatGPT eats STA130: Introduction to Statistical Reasoning and Data Science

• Google "uoft jupyterhub" -> https://datatools.utoronto.ca
  • Choose "jupyter" https://jupyter.utoronto.ca/ -> and then created a "New Python 3 (ipykernel)" to open a notebook
• Get ChatGPT 3.5 or better yet 4.0

	Topic	TUT(Friday)	LEC(Monday)	Draft	Reviewer
01	Data Wrangling	Sep06	Sep09	Scott	Shiraz+Ray
02	Coding	Sep13	Sep16	Scott	Edric+Serena
03	Visualization	Sep20	Sep23	Scott	Ali+Alex
04	Bootstrapping	Sep27	Sep30	Ali	Alex
05	One Sample HT	Oct04	Oct07	Alex	Ali
--	Review/Thnxgiv	Oct11	Oct14
--	Midterm Exam	Oct18
06	Regression I	-->	Oct21	Shiraz	Serena
06	Coefficient HT	Oct25	<--	Shiraz	Alex
--	Reading Week		Oct28
--	Reading Week	Nov01
56	Two Sample HT		Nov04
07	Regression II	Nov08	Nov11	Serena	Shiraz
08	Classification	Nov15	Nov18	Ray	Edric
09	Ethics	Nov22	Nov25	Edric	Ray
10	Review		Dec02
11	Projects		Dec03(Tuesday)

Learning Objectives

1. Week 1
   1. ChatGPT
      1. can be very helpful both in terms of coding and conceptual understanding
      2. can make mistakes
      3. can be influenced by how it is engaged with
   2. jupyter notebooks
      1. for python coding
      2. and Markdown formatting
   3. GitHub.com as a repository for coding files
   4. Data Wrangling
      1. importing libraries import pandas as pd
      2. loading data pd.read_csv() # file or url
      3. examining missingness df.isnull().sum()
      4. removing missingness df.dropna() and del df['col']
      5. summarizing data pd.describe()
      6. mean, variance, standard deviation
      7. group by df.groupby.describe()
      8. subsetting `df[], df.loc[], df.iloc[]
      9. boolean selection