- Home
- Syllabus
- Schedule
- Resources
-
Lectures
- Notes
- 01 - Yawning
- 02 - Data & Sampling
- 03 - Experimental Design
- 04 - Center, Shape, and Spread
- 05 - Bivariate Relationships
- 06 - Linear Regression
- 07 - Linear Fit
- 08 - Outliers, Leverage, and Influence
- 09 - Multiple Regression
- 10 - Randomization Test
- 11 - Hypothesis Testing
- 12 - Simulation
- 13 - Normal Distribution
- 14 - Confidence Intervals
- 15 - More on Confidence Intervals
- 16 - Probability
- 17 - Conditional Probability
- 18 - Random Variables
- 19 - Inference for a Single Proportion
- 20 - Difference of two Proportions
- 21 - Goodness of Fit
- 22 - Independence
- 23 - Inference for a Mean
- 24 - Difference of Two Means
- 25 - ANOVA
- 26 - The Bootstrap
- 27 - Inference for Regression
- 28 - Bootstrap for Regression
- 29 - Regression Diagnostics
-
Sources
- 01 - Yawning
- 02 - Data & Sampling
- 03 - Experimental Design
- 04 - Center, Shape, and Spread
- 05 - Bivariate Relationships
- 06 - Linear Regression
- 07 - Linear Fit
- 08 - Outliers, Leverage, and Influence
- 09 - Multiple Regression
- 10 - Randomization Test
- 11 - Hypothesis Testing
- 12 - Simulation
- 13 - Normal Distribution
- 14 - Confidence Intervals
- 15 - More on Confidence Intervals
- 16 - Probability
- 17 - Conditional Probability
- 18 - Random Variables
- 19 - Inference for a Single Proportion
- 20 - Difference of two Proportions
- 21 - Goodness of Fit
- 22 - Independence
- 23 - Inference for a Mean
- 24 - Difference of Two Means
- 25 - ANOVA
- 26 - The Bootstrap
- 27 - Inference for Regression
- 28 - Bootstrap for Regression
- 29 - Regression Diagnostics
-
Labs
- Labs
- Introduction to R and RStudio
- Introduction to Data
- Simple Linear Regression
- Sampling Distributions
- Confidence Intervals
- Probability
- Inference for Categorical Data
- Inference for Numerical Data
- Normal Distribution
- Multiple Regression
- Lab Sources
- Introduction to R and RStudio
- Introduction to Data
- Simple Linear Regression
- Sampling Distributions
- Confidence Intervals
- Probability
- Inference for Categorical Data
- Inference for Numerical Data
- Normal Distribution
- Multiple Regression
- Lab Templates
- File -> New File -> R Markdown...
- Lab CSS
-
Assignments
- Homework
- All Homework Assignments
- Exams
- Project
- Instructions
- Schedule
- Advice
MTH/SDS 220
Welcome to MTH/SDS 220: Introduction to Probability and Statistics. You will find most of the course content here, but please keep an eye on Moodle for grades and assignments.
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Created by Ben Baumer.