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
Sep 25, Mon Introduction to PSYC 201
Sep 27, Wed Lesson 1.1: Data–where it comes from and why it matters
Sep 29, Fri Lab 1: Intro to R and RStudio
  R CheatSheet
Oct 2, Mon Quiz 1 in class
  Lesson 1.2: Exploratory Data Analysis
Oct 4, Wed Lesson 1.3: More Exploratory Data Analysis
  Example Exploratory Data Analysis
Oct 6, Fri Lab 2: Intro to Data
Due dates
  • CAOS PreTest: Sep 30 11:55PM
  • Lab 1: Oct 6, Start of Lab Section
  • Lab 2: Oct 13, Start of Lab Section
  • Problem Set 1: Oct 9, 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 9, Mon Quiz 2 in class
  Lesson 2.1: Randomization and Sampling
  Simulating Gender Discrimination in Hiring
Oct 11, Wed Lesson 2.2: Hypothesis Testing
  Simulating Cardiac Arrest Outcomes
Oct 13, Fri Lab 3: Testing the Hot Hands Hypothesis
Oct 16, Mon Quiz 3 in class
  Lesson 2.3: The Central Limit Theorem
Oct 18, Wed Lesson 2.4: The Normal Distribution and more on the Central Limit Theorem
Oct 20, Fri Lab 4: Sampling Distributions
Oct 23, Mon Quiz 4 in class
  Lesson 2.5: Confidence Intervals
Due dates
  • Lab 3: Oct 21, Start of Lab Section
  • Lab 4: Oct 27, Start of Lab Section
  • PS 2: Oct 25, 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 25, Wed Lesson 3.1: Inference for a Single Proportion
  Simulating population proportion estimates
Oct 27, Fri Lab 5: Confidence Intervals
Oct 30, Mon Quiz 5 in class
  Lesson 3.2: Difference of Two Proportions
Nov 1, Wed Lesson 3.3: The t-distribution
  Simulating Friday the 13th
Nov 3, Fri Lab 6: Inference for Categorical Data
Nov 6, Mon Quiz 6 in class
  Lesson 3.4: Paired data and the t-tests
  Simulating reading and writing score differences
Nov 8, Wed Lesson 3.5: Difference of two means
Nov 10, Fri Lab 7: Inference for Numerical Data
Due dates
  • Lab 5: Nov 3, Start of Lab Section
  • Lab 6: Nov 10, Start of Lab Section
  • Lab 7: Nov 17, Start of Lab Section
  • PS 3: Nov 13, 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 13, Mon Quiz 7 in class
  Lesson 4.1: Linear Regression
Nov 15, Wed Lesson 4.2: Residuals and Least Squares
Nov 17, Fri Lab 8: Simple Linear Regression
Nov 20, Mon Quiz 8 in class
  Lesson 4.3: Inference for linear regression
Nov 22, Wed Lesson 4.4: Multiple regression
  Understanding correlation and simple regression
Nov 24, Fri Thankgsiving Break - no class
Nov 27, Mon Quiz 9 in class
  Lesson 4.5: Model Selection
Nov 29, Wed Lesson 4.6 Multiple Regression and ANOVA
  Regression and ANOVA
Dec 1, Fri Lab: Work on project (Optional)
Due dates
  • Lab 8: Dec 1, Start of Lab Section
  • PS 4: Dec 4 Mon, 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 7 11:55PM
  • CAOS PostTest: Dec 7 11:55PM

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