Jump to: | Unit 1 | Unit 2 | Unit 3 | Unit 4 Unit 5 Unit 6 |

Learning objectives: L0 1 | Textbook: Chp 1 | Videos: Videos 1 |

Jan 13, Mon | Introduction to 85-309 |

Jan 15, Wed | Lesson 1.1: Data–where it comes from and why it matters |

Jan 17, Fri | Lab 1: Intro to R and RStudio |

Jan 20, Mon | Martin Luther King Day – no class |

Jan 22, Wed | Quiz 1 in class |

Lesson 1.2: Exploratory Data Analysis | |

Jan 24, Fri | Lab 2: Intro to Data |

Jan 27, Mon | Lesson 1.3: More Exploratory Data Analysis |

Exploring class data |

- CAOS PreTest: Jan 18 11:55PM
- Lab 1: Jan 24, Fri, at 1:30pm
- Lab 2: Jan 31, Fri, at 1:30pm
- Problem Set 1: Jan 29, Wed, at 1:30pm
- End of chapter exercises from
**Chp 1**. Only turn in answers to graded questions, use the back of the book to check your work on the practice questions. Must show**all**work to get credit. Submit homework through Canvas. **Graded questions:**1.2, 1.12, 1.20, 1.30, 1.34, 1.42- Practice questions:
- Part 1 – Designing studies: 1.1, 1.3, 1.9, 1.11, 1.13, 1.19
- Part 2 – Examining Data: 1.25, 1.27, 1.29, 1.37, 1.39, 1.41, 1.47

- End of chapter exercises from

Learning objectives: LO 2 | Textbook: Chp 2 |

Jan 29, Wed | Quiz 2 in class |

Lesson 2.1: Randomization and Sampling | |

Discrimination in Hiring | |

Jan 31, Fri | Lab 3: Intro to the Tidyverse and Functions |

Feb 3, Mon | Lesson 2.2: Hypothesis Testing |

Cardiac Arrest | |

Feb 5, Wed | Quiz 3 in class |

Lesson 2.3: The Central Limit Theorem | |

Feb 7, Fri | Lab 4: Testing the Hot Hands Hypothesis |

Feb 10, Mon | Lesson 2.4: The Normal Distribution and more on the Central Limit Theorem |

QQ Plots | |

Feb 12, Wed | Quiz 4 in class |

Lesson 2.5: Confidence Intervals | |

Feb 14, Fri | Lab 5: Sampling Distributions |

Eberly Center Early Course Feedback Form |

- Lab 3: Feb 7, Fri, at 1:30pm
- Lab 4: Feb 14, Fri, at 1:30pm
- Lab 5: Feb 21, Fri, at 1:30pm
- PS 2: Feb 17, Mon, at 1:30 PM
- End of chapter exercises from
**Chp 2**. Only turn in answers to graded questions, use the back of the book to check your work on the practice questions. Must show**all**work to get credit. Submit homework through Canvas. **Graded questions:**2.4, 2.10, 2.16, 2.18, 2.24, 2.38- Practice questions:
- Part 1 – Randomization and Hypothesis Testing: 2.1, 2.3, 2.5, 2.9,
- Part 2 – The Normal Distribution: 2.11, 3.13, 2.15, 2.17, 2.19, 2.23, 2.29, 2.31
- Part 3 - Applying the Normal model 2.35, 2.37

- End of chapter exercises from

Learning objectives: L0 3 | Textbook: Chp 3 and Chp 4 |

Feb 17, Mon | Lesson 3.1: Inference for a Single Proportion |

Scientific Literacy | |

Feb 19, Wed | Quiz 5 in class |

Lesson 3.2: Inference for the difference of two proportions | |

Feb 21, Fri | Lab 6: Confidence Intervals |

Feb 24, Mon | Lesson 3.3: The t-distribution |

t-tests | |

Feb 26, Wed | Quiz 6 in class |

Lesson 3.4: Difference of two means | |

Feb 28, Fri | Lab 7: Inference for Categorical Data |

Mar 2, Mon | 3.5: Difference of many means |

Dictator game | |

Mar 4, Wed | Quiz 7 in class |

Mid-semester Review | |

ANOVA example |

- Lab 6: Feb 28, Fri, at 1:30 PM
- Lab 7: Mar 6, Fri, at 1:30 PM
- PS 3: Mar 23, Mon, at 1:30 PM
- End of chapter exercises from
**Chp 3 and 4**of Intro to Stats with Randomization and Simulation. Only turn in answers to graded questions, use the back of the book to check your work on the practice questions. Must show**all**work to get credit. Submit homework through Canvas. **Graded questions:**3.2, 3.12, 3.24, 4.6, 4.10, 4.14, 4.18- Practice questions:
- Part 1 – Inference for a single proportion: 3.1, 3.5, 3.11, 3.19
- Part 2 – Difference of two proportions: 3.23, 3.25, 2.15, 2.17, 2.19, 2.23, 2.29, 2.31
- Part 3 - One-sample means with t-tests 4.3, 4.5
- Part 4 - Paired data: 4.9, 4.13
- Part 5 - Difference of two means: 4.15, 4.17, 4.23

- End of chapter exercises from

Mar 6, Fri | Mid-Semester Break - no class |

Mar 9, Mon | Spring Break - no class |

Mar 11, Wed | Spring Break - no class |

Mar 13, Fri | Spring Break - no class |

Learning objectives: LO 4 | Textbook: Chp 5 |

Mar 16, Mon | Class Canceled |

Mar 18, Wed | Lesson 4.1: Linear Regression |

Correlation | |

Mar 20, Fri | Lab 8: Inference for Numerical Data |

Mar 23, Mon | Lesson 4.2: Residuals and Least Squares |

Mar 25, Wed | Quiz 8 in class |

Lesson 4.3: Inference for linear regression | |

Mar 27, Fri | Lab 9: Introduction to Linear Regression |

- Lab 8: Mar 27, Fri, at 1:30 PM
- Lab 9: Apr 3, Fri, at 1:30 PM
- PS 4: Apr 1 Wed, at 1:30 PM
- End of chapter exercises from
**Chp 5**of Intro to Stats with Randomization and Simulation. Only turn in answers to graded questions, use the back of the book to check your work on the practice questions. Must show**all**work to get credit. Submit homework through Canvas. **Graded questions:**5.4, 5.10, 5.20, 5.22, 5.28, 5.34- Practice questions:
- Part 1 – Line fitting, residuals, and correlation: 5.1, 5.3, 5.9
- Part 2 – Fitting a line by least squares: 5.17, 5.19
- Part 3 - Types of Outliers in linear regression: 5.23, 5.25
- Part 4 - Inference for linear regression: 5.27, 5.29, 5.33

- End of chapter exercises from

Learning objectives: LO 5 | Textbook: Chp 6 |

Mar 30, Mon | Lesson 5.1: Multiple Regression |

April 1, Wed | Quiz 9 in class |

April 3, Fri | Lab 10: Multiple Linear Regression |

April 6, Mon | Lesson 5.2: Model Selection |

Stepwise Regression | |

April 8, Wed | Quiz 10 in class |

Lesson 5.3 Transformations | |

Transformations | |

April 10, Fri | Lab 11: Choosing the right model |

April 13, Mon | Lesson 5.4 The Generalized Linear Model |

Logistic Regression | |

April 15, Wed | Quiz 11 in class |

Lesson 5.5 Hierarchical Models and Mixed effects | |

April 17, Fri | Optional Review |

- Lab 10: Apr 10, Fri, at 1:30 PM
- Lab 11: Apr 24, Fri, at 1:30 PM
- PS 4: Apr 20 Mon, at 1:30 PM
- End of chapter exercises from
**Chp 6**of Intro to Stats with Randomization and Simulation. Only turn in answers to graded questions, use the back of the book to check your work on the practice questions. Must show**all**work to get credit. Submit homework through Canvas. **Graded questions:**6.2, 6.4, 6.8, 6.12, 6.14- Practice questions:
- Part 1 - Introduction to multiple regression: 6.1, 6.3
- Part 2 - Model selection: 6.7, 6.9
- Part 3 - Checking Model Assumptions: 6.11
- Part 4 - Logistic Regression: 6.13, 6.15

- End of chapter exercises from

Learning objectives: LO 6 |

April 20, Mon | What is Probability? | |

April 22, Wed | Bayesian inference | |

April 24, Fri | Introducing the final project | |

April 27, Mon | Graphical models | |

Bayesian linear regression | ||

April 29, Wed | [Language learning as Bayesian inference | (post/slides/bayesian_learning.html) |

May 1, Fri | Work on final projects–optional |

- CAOS PostTest: May 1 11:55PM
- Final Project : May 8 11:55PM