Schedule


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Unit 1 - Introduction to data

Resources
Videos: Videos for Unit 1 Learning objectives: LO 1 Textbook: Chp 1
Class / lab
Aug 24, Mon Introduction to Sta 101    
  Lesson 1.1: Data Collection, observational studies & experiments    
Aug 26, Wed RA 1 in class (not graded)
  Lesson 1.2: Exploratory data analysis    
  App Ex 1.1: Distributions of numerical variables
Aug 27, Thu Lab 0: Introduction
Aug 31, Mon Lesson 1.3: Introduction to statistical inference    
Sep 2, Wed Lesson 1.4: Review of Unit 1    
  App Ex 1.2: Scientific studies in the press
  App Ex 1.3: Histogram to boxplot
  App Ex 1.4: Randomization testing
Sep 3, Thu Lab 1: Intro to R and RStudio
Due dates
  • PS 1: Sep 4, Fri
    • 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. Click here to submit the problem set.
    • Graded questions: 1.2, 1.6, 1.12, 1.20, 1.32, 1.34, 1.44, 1.52, 1.56, 1.60, 1.64, 1.66, 1.68, 1.70 (see errata)
    • Practice questions:
      • Part 1 – Designing studies: 1.1, 1.3, 1.11, 1.13, 1.17, 1.19, 1.25, 1.27, 1.31
      • Part 2 – Exploratory data analysis: 1.39, 1.41, 1.45, 1.49, 1.51, 1.55, 1.59, 1.63, 1.65
      • Part 3 – Introduction to inference via simulation: 1.67, 1.69
  • PA 1: Sep 6, Sun
    • Take between Sep 2, Wed and Sep 6, Sun.
    • You have 30 minutes to complete. Only one attempt allowed. Click here to take the performance assessment.

Unit 2 - Probability and distributions

Resources
Videos: Videos for Unit 2 Learning objectives: LO 2 Textbook: Chp 2 - Sec 2.1, 2.2 + Chp 3 - Sec 3.1, 3.2, 3.4
In class / lab
Sep 7, Mon RA 2 in class
  Lesson 2.1: Probability and conditional probability    
  App Ex 2.1: Voting probabilities of college students
Sep 9, Wed Lesson 2.2: Bayes’ theorem and Bayesian inference    
  App Ex 2.2: Bayesian drug testing
Sep 10, Thu Lab 2: Introduction to data
Sep 14, Mon Lesson 2.3: Normal distribution    
  App Ex 2.3: Normal distribution
Sep 16, Wed Lesson 2.4: Binomial distribution    
  App Ex 2.4: Binomial distribution
Sep 17, Thu Lab 3: Probability
Due dates
  • Lab 1: Sep 10, Thu
  • Lab 2: Sep 17, Thu
  • PS 2: Sep 18, Fri
    • End of chapter exercises from Chp 2 and Chp 3. 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. Click here to submit the problem set.
    • Graded questions:
      • Chp 2: 2.2, 2.8, 2.18, 2.20, 2.22, 2.26
      • Chp 3: 3.4, 3.6, 3.12, 3.18, 3.26, 3.28, 3.30, 3.36
    • Practice questions:
      • Part 1 – Defining probability: 2.1, 2.3, 2.5, 2.7, 2.13
      • Part 2 – Conditional probability: 2.15, 2.19, 2.21, 2.23
      • Part 3 – Normal distribution: 3.3, 3.5, 3.9, 3.11, 3.17
      • Part 4 – Binomial distribution: 3.25, 3.27, 3.29, 3.33
  • PA 2: Sep 20, Sun
    • Take between Sep 16, Wed and Sep 20, Sun.
    • You have 30 minutes to complete. Only one attempt allowed. Click here to take the performance assessment.

Unit 3 - Foundations for inference

Resources
Videos: Videos for Unit 3 Learning objectives: LO 3 Textbook: Chp 4
In class / lab
Sep 21, Mon RA 3 in class
  Lesson 3.1: Variability in estimates and CLT    
Sep 23, Wed Lesson 3.2: Confidence intervals    
  App Ex 3.1: Relaxing after work
Sep 24, Thu Lab 4: Sampling distributions
Sep 28, Mon Lesson 3.3: Hypothesis tests    
  App Ex 3.2: Grade inflation
Sep 30, Wed Lesson 3.4: Review    
Oct 1, Thu Lab 5: Confidence intervals
Due dates
  • Lab 3: Sep 24, Thu
  • Lab 4: Oct 1, Thu
  • PS 3: Oct 2, Fri
    • End of chapter exercises from Chp 4. 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. Click here to submit the problem set.
    • Graded questions: 4.2, 4.8, 4.10, 4.12, 4.16, 4.20, 4.24, 4.28, 4.30, 4.32, 4.36, 4.38, 4.44, 4.48
    • Practice questions:
      • Part 1 – Variability in estimates and the Central Limit Theorem: 4.1, 4.3, 4.5, 4.33, 4. 35, 4.37, 4.41
      • Part 2 – Confidence intervals: 4.9, 4.11, 4.13, 4.15
      • Part 3 – Hypothesis tests: 4.17, 4.19, 4.23, 4.25, 4.27
      • Part 4 – Inference for other estimators: 4.43, 4.45
      • Part 5 - Decision errors, significance, and confidence: 4.29, 4.31, 4.47
  • PA 3: Oct 4, Sun
    • Take between Sep 30, Wed and Oct 4, Sun.
    • You have 30 minutes to complete. Only one attempt allowed. Click here to take the performance assessment.

Midterm 1 - Oct 5, Mon (in class)


Unit 4 - Inference for numerical variables

Resources
Videos: Videos for Unit 4 Learning objectives: LO 4 Textbook: Chp 5
In class / lab
Oct 7, Wed Lesson 4.1: Inference with t    
  App Ex 4.1: Comparing means
Oct 8, Thu Lab 6: Inference for numerical data
Oct 12, Mon Fall Break - no class
Oct 14, Wed RA 4 in class
  Lesson 4.2: Bootstrap intervals    
  App Ex 4.2: Bootstrap intervals
Oct 15, Thu Work on Project 1 proposal
Oct 19, Mon Lesson 4.3: Power    
  App Ex 4.3: Power
Oct 21, Wed Lesson 4.4: ANOVA    
  App Ex 4.4: ANOVA
Oct 22, Thu Lab 7: (More) inference for numerical data
Due dates
  • Lab 5: Oct 8, Thu
  • Lab 6: Oct 15, Thu
  • Project 1 Proposal: Oct 19, Mon
  • PS 4: Oct 23, Fri
    • End of chapter exercises from Chp 5. 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. Click here to submit the problem set.
    • Graded questions: Chp 5: 5.4, 5.6, 5.12, 5.16, 5.20, 5.28, 5.30, 5.34, 5.36, 5.38, 5.44, 5.46, 5.48, 5.50
    • Practice questions:
      • Part 1 – t-inference: 5.1, 5.3, 5.5, 5.13, 5.17, 5.19, 5.21, 5.23, 5.27, 5.31, 5.35, 5.37
      • Part 2 – Power: 5.39
      • Part 3 – Comparing three or more means (ANOVA): 5.41, 5.43, 5.45, 5.47, 5.49, 5.51
      • Part 4 – Simulation based inference for means
  • PA 4: Oct 25, Sun
    • Take between Oct 21, Wed and Oct 25, Sun.
    • You have 30 minutes to complete. Only one attempt allowed. Click here to take the performance assessment.

Unit 5 - Inference for categorical variables

Resources
Videos: Videos for Unit 5 Learning objectives: LO 5 Textbook: Chp 6
In class / lab
Oct 26, Mon RA 5 in class
  Lesson 5.1: Inference for a single proportion    
  App Ex 5.1: Inference for a single proportion
Oct 28, Wed Lesson 5.2: Inference for comparing two proportions    
  App Ex 5.2: Inference for comparing two proportions
Oct 29, Thu Lab 8: Inference for categorical data
Nov 2, Mon Lesson 5.3: Chi-square tests    
  App Ex 5.3: Chi-square tests
Nov 4, Wed Lesson 5.4: Review/synthesis    
Nov 5, Thu Work on Project 1
Due dates
  • Lab 7: Oct 29, Thu
  • Lab 8: Nov 5, Thu
  • Project 1: Nov 6, Fri
  • PS 5: Nov 6, Fri
    • End of chapter exercises from Chp 6. 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. Click here to submit the problem set.
    • Graded questions: 6.2, 6.4, 6.8, 6.12, 6.16, 6.20, 6.26, 6.28, 6.30, 6.36, 6.44, 6.48, 6.52, 6.54, 6.56
    • Practice questions:
      • Part 1 – Single proportion: 6.1, 6.3, 6.5, 6.9, 6.11, 6.13, 6.15, 6.19, 6.21
      • Part 2 – Comparing two proportions: 6.23, 6.25, 6.27, 6.29, 6.31, 6.33, 6.35
      • Part 3 – Inference for proportions via simulation: 6.51, 6.53, 6.55
      • Part 4 – Comparing three or more proportions (Chi-square): 6.39, 6.41, 6.43, 6.45, 6.47
  • PA 5: Nov 7, Sat (Note day change to allow for reviewing answers before the midterm)
    • Take between Nov 4, Wed and Nov 7, Sat.
    • You have 30 minutes to complete. Only one attempt allowed. Click here to take the performance assessment.

Midterm 2 - Nov 9, Mon (in class)

  • Covers Units 4 and 5 + fundamentals from Units 1 - 3
  • Sample Midterm 2: handout + solutions

Unit 6 - Introduction to linear regression

Resources
Videos: Videos for Unit 6 Learning objectives: LO 6 Textbook: Chp 7
In class / lab
Nov 11, Wed RA 6 in class
  Lesson 6.1: Introduction to regression    
  App Ex 6.1: Linear models
Nov 12, Thu Lab 9: Introduction to linear regression
Nov 16, Mon Lesson 6.2: Outliers and inference for regression    
  App Ex 6.2: Linear regression
Due dates
  • PS 6: Nov 20, Fri
    • End of chapter exercises from Chp 7. 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. Click here to submit the problem set.
    • Graded questions: 7.2, 7.6, 7.8, 7.10, 7.12, 7.14, 7.16, 7.18, 7.20, 7.26, 7.28, 7.30, 7.34, 7.36, 7.42, 7.44
    • Practice questions:
      • Part 1 – Relationship between two numerical variables: 7.1, 7.3, 7.7, 7.9, 7.11, 7.13, 7.15
      • Part 2 – Linear regression with a single predictor: 7.17, 7.19, 7.25, 7.27, 7.29, 7.31, 7.33
      • Part 3 – Inference for linear regression: 7.25, 7.37, 7.39, 7.41, 7.43
  • PA 6: Nov 22, Sun
    • Take between Nov 16, Mon and Nov 22, Sun.
    • You have 30 minutes to complete. Only one attempt allowed. Click here to take the performance assessment.

Unit 7 - Multiple linear regression

Resources
Videos: Videos for Unit 7 Learning objectives: LO 7 Textbook: Chp 8 - Sec 8.1, 8.2, 8.3
In class / lab
Nov 18, Wed RA 7 in class
  Lesson 7.1: Introduction to multiple linear regression    
Nov 19, Thu Lab 10: Multiple linear regression
Nov 23, Mon Lesson 7.2: Model selection & diagnostics for MLR    
  App Ex 7.1: Multiple linear regression
Nov 25, Wed Thanksgiving break - no class
Nov 26, Thu Thanksgiving break - no lab
Nov 30, Mon Lesson 7.3: Transformations and case study    
  App Ex 7.2: Interpreting models with a transformed response
Due dates
  • Lab 8: Nov 19, Thu
  • Lab 10: Nov 30, Mon (by class, 10:05am)
  • PS 7: Dec 4, Fri
    • End of chapter exercises from Chp 8. 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. Click here to submit the problem set.
    • Graded questions: 8.2, 8.4, 8.6, 8.8, 8.10, 8.12, 8.14
    • Practice questions:
      • Part 1 – Regression with multiple predictors: 8.1, 8.3
      • Part 2 – Inference for MLR: 8.5
      • Part 3 – Model selection: 8.7, 8.9, 8.11
      • Part 4 – Model diagnostics: 8.13
  • PA 7: Dec 6, Sun
    • Take between Nov 30, Mon and Dec 6, Sun.
    • You have 30 minutes to complete. Only one attempt allowed. Click here to take the performance assessment.

Wrap up

In class / lab
Dec 2, Wed Review / synthesis    
Dec 3, Thu Project 2 poster session (@ The Edge Workshop Room)

Final Exam - Dec 10, Thu (2-5pm)

  • Cumulative, covers Units 1 - 7
  • Practice problems for Final: handout + solutions