Math221D Notebook
Getting Started
Course Introduction
Installing R
Introducing R
Installing R Libraries
The Statistical Process
Statistical Process Practice Problems
Response and Explanatory Variables
Descriptive Stats
Descriptive Statistics
Numerical Quantitative Data Summaries
Practice: Numerical Summaries (Quant.)
Graphical Quantitative Data Summaries
Practice: Graphical Summaries (Quant.)
Quantitative Data Summaries - Multiple Groups
Practice: Summarizing Multiple Groups
Summarizing Bivariate Data
Practice: Bivariate Data
Categorical Data Summaries - One Variable
Categorical Data Summaries - 2 Variables
Practice: Summarizing Categorical Data
Data Wrangling
Into the Tidyverse
A Better Way to Plot
Intro to Data Wrangling
filter()
select()
mutate()
Factors in R
Into The Tidyverse
Data Wrangling - Application Activity
Bonus Material
Level up your Tidy-ness
group_by() + summarise()
Inferential Stats
Foundations
Probability
The Normal Distribution
Normal Probability Practice
Distribution of Sample Means
Assessing Normality
Central Limit Theorem Practice
Introducing Hypothesis Tests
Statistical Significance
Statistical Tests I
Confidence Intervals for a Mean
Confidence Intervals For Means - Practice
One-Sample T-test
Don’t Take it Personally
Confidence Intervals and Hypothesis Tests for Proportions
Confidence Intervals and Hypothesis Tests Practice
Independent Two-sample T-test
2-Sample Independent T-Test Practice
Matched Pairs T-test
Matched Pairs T-Test Practice
2-Sample Proportions
2-Sample Proportion Practice
Statistical Tests II
Simple Linear Regression
Regression Practice
Analysis of Variance (ANOVA)
ANOVA Practice
Chi-square Test of Independence
Chi-Square Practice
Semester Project
Finding a Dataset
Downloading Data
Semester Project
Semester Project
Resources
Interactive Course Map
Hypothesis Test Process
Tidyverse Cheat Sheet
R for Data Science
Statistics Notebook - R Commands
Interactive Course Map
Here’s the course‑map tool which can be found here:
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