Schedule

Jump to:     Unit 1         Unit 2         Unit 3         Unit 4    

Unit 1 - Introduction to data

Resources
Learning objectives: L0 1 Textbook: Chp 1 Videos: Videos 1
Class / lab
Oct 1, Mon Introduction to PSYC 201
Oct 3, Wed Lesson 1.1: Data–where it comes from and why it matters
Oct 5, Fri Lab 1: Intro to R and RStudio
  R CheatSheet
Oct 8, Mon Quiz 1 in class
  Lesson 1.2: Exploratory Data Analysis
Oct 10, Wed Lesson 1.3: More Exploratory Data Analysis
  Example Exploratory Data Analysis
Oct 12, Fri Lab 2: Intro to Data
Due dates
  • CAOS PreTest: Oct 9 11:55PM
  • Lab 1: Oct 12, Start of Lab Section
  • Lab 2: Oct 19, Start of Lab Section
  • Problem Set 1: Oct 15, Mon, at 12:30pm
    • 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 Google Classroom.
    • 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

Unit 2 - Foundations for Inference

Resources
Learning objectives: LO 2 Textbook: Chp 2
Class / lab
Oct 15, Mon Quiz 2 in class
  Lesson 2.1: Randomization and Sampling
  Simulating Bias in Hiring
Oct 17, Wed Lesson 2.2: Hypothesis Testing
  Simulating Cardiac Arrest Outcomes
  Hypothesis Testing Lab Primer
Oct 19, Fri Lab 3: Testing the Hot Hands Hypothesis
Oct 22, Mon Quiz 3 in class
  Lesson 2.3: The Central Limit Theorem
Oct 24, Wed Lesson 2.4: The Normal Distribution and more on the Central Limit Theorem
Oct 26, Fri Lab 4: Sampling Distributions
Oct 29, Mon Quiz 4 in class
  Lesson 2.5: Confidence Intervals
Due dates
  • Lab 3: Oct 26, Start of Lab Section
  • Lab 4: Nov 2, Start of Lab Section
  • PS 2: Oct 31, 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 Google Classroom.
    • 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

Unit 3 - Inference for Categorical and Numerical Data

Resources
Learning objectives: L0 3 Textbook: Chp 3 and Chp 4
Class / lab
Oct 31, Wed Lesson 3.1: Inference for a Single Proportion
Nov 2, Fri Lab 5: Confidence Intervals
Nov 5, Mon Quiz 5 in class
Nov 7, Wed Lesson 3.3: The t-distribution
Nov 9, Fri Lab 6: Inference for Categorical Data
Nov 12, Mon Quiz 6 in class
  Lesson 3.4: Paired data and the t-tests
Nov 14, Wed Lesson 3.5: Difference of two means
Nov 16, Fri Lab 7: Inference for Numerical Data
Due dates
  • Lab 5: Nov 9, Start of Lab Section
  • Lab 6: Nov 16, Start of Lab Section
  • Lab 7: Nov 30, Start of Lab Section
  • PS 3: Nov 19, 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 Google Classroom.
    • 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

Unit 4 - Regression and Prediction

Resources
Learning objectives: LO 4 Textbook: Chp 5 and 6
Class / lab
Nov 19, Mon Quiz 7 in class
  Lesson 4.1: Linear Regression
Nov 21, Wed Lesson 4.2: Residuals and Least Squares
Nov 23, Fri Thanksgiving Break - no class
Nov 26, Mon Quiz 8 in class
  Lesson 4.3: Inference for linear regression
Nov 28, Wed Lesson 4.4: Multiple regression
Nov 30, Fri Lab 8: Simple Linear Regression
Dec 3, Mon Quiz 9 in class
  Lesson 4.5: Model Selection
Dec 5, Wed Lesson 4.6 Multiple Regression and ANOVA
Dec 7, Fri Lab: Work on project (Optional)
Due dates
  • Lab 8: Dec 7, Start of Lab Section
  • PS 4: Dec 7 Fri, 12:30 PM
    • End of chapter exercises from Chp 5 and 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 Google Classroom.
    • Graded questions: 5.4, 5.10, 5.20, 5.28, 6.2, 6.8,
    • 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 - Inference for linear regression: 5.27, 5.29
      • Part 4 - Introduction to multiple regression: 6.1, 6.3
      • Part 5 - Model selection: 6.7, 6.9, 6.11
  • Final Project : Dec 13 11:55PM
  • CAOS PostTest: Dec 13 11:55PM

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