• # Sta 101 - Data Analysis and Statistical Inference (Fall 2015)

## Schedule

### 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.
• 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.

### 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