Data 88S: Probability and Mathematical Statistics for Data Science

UC Berkeley, Summer 2023

Week 8

Aug 7
  • The homework on last week’s material, Homework 7 is due Monday, August 7th, at 11:59 PM. There are NO extensions on Homework 7.
  • The final is on Thursday, August 10th at 10:30AM - 1:30PM in McCone 141. It will cover Chapters 1 through 11. Please see #126 on Ed.

Calendar

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Week 1: The Fundamentals

Jun 19
Juneteenth Holiday
Jun 20
Lecture 1 Fundamentals, exact calculations, and bounds
Syllabus, Ch 1.1 - 1.2
Homework 1
Due Jun 26 at 11:59 PM
Section 1
Ch 1 Ex 1, 3, 5, 2, 4
Jun 21
Lecture 2 The rules; intersections and conditioning
Ch 1.3, 2.1 - 2.2
Jun 22
Lecture 3 Updating chances; independence
Ch 2.3 - 2.5
Section 2
Ch 2 Ex 7, 5, 10, 4, 11, 6

Week 2: Random Variables and Random Counts

Jun 26
Lecture 4 Random variables
Ch 3.1 - 3.2
Homework 2
Due Jul 3 at 11:59 PM
Jun 27
Lecture 5 Random counts: binomial
Ch 3.3
Section 3
Ch 3 Ex 1, 2, 7, 9, 3, 8
Jun 28
Lecture 6 Random counts: hypergeometric
Ch 3.4 - 3.5
Jun 29
Lecture 7 Exponential approximations; geometric
Ch 4.1 - 4.3
Quiz 1
Ch 1 and 2
Section 4
Ch 3 Ex 6, 10; Ch 4, Ex 4, 6, 5

Week 3: The Poisson Distribution and Expectation

Jul 3
Lecture 8 Law of small numbers; Poisson
Ch 4.4
Homework 3
Due Jul 10 at 11:59 PM
Jul 4
Independence Day Holiday
Jul 5
Lecture 9 Expectation and additivity
Ch 5.1 - 5.3
Jul 6
Lecture 10 Unbiased estimators
Ch 5.4
Quiz 2
Ch 3 and 4.1 - 4.3
Section 5
Ch 4, Ex 7c, 6; Ch 5, Ex 4, 6, 9, 11, 7

Week 4: Conditioning and Variance

Jul 10
Lecture 11 Expectation by conditioning
Ch 5.5 - 5.6
Homework 4
Due Jul 17 at 11:59 PM
Jul 11
Lecture 12 Standard deviation; tail bounds
Ch 6.1 - 6.4
Section 6
Ch 5, Ex 13, 14, 15; Ch 6, Ex 2, 4, 7, 5
Jul 12
Lecture 13 Variance and additivity: binomial and hypergeometric
Ch 7.1 - 7.2
Jul 13
Lecture 14 Large samples: law of large numbers
Ch 7.3
Quiz 3
Ch 4.4 and 5.1 - 5.4
Section 7
Ch 7, Ex 1, 3, 9, 4, 8; Law of Averages Question (not in textbook)

Week 5: The Central Limit Theorem, Hypothesis Testing, and Densities

Jul 17
Lecture 15 Central Limit Theorem
Ch 8.1 - 8.4
Homework 5
Due Jul 24 at 11:59 PM
Jul 18
Lecture 16 Confidence intervals
Ch 9.1 - 9.2
Section 8
Ch 8, Ex 1, 2, 3, 4; Ch 9, Ex 1, 2, 4
Jul 19
Lecture 17 Testing hypotheses
Ch 9.3 - 9.4
Jul 20
Lecture 18 Probability density
Ch 10.1
Quiz 4
Ch 5.5 - 5.6, 6, and 7
Section 9
Ch 9, Ex 5, 9, 7, 8, 10; Integration Practice (not in textbook)

Week 6: Densities and Estimation

Jul 24
Lecture 19 Expectation and variance revisited
Ch 10.2
Homework 6
Due Jul 31 at 11:59 PM
Jul 25
Lecture 20 The exponential distribution
Ch 10.3
Section 10
Ch 10, Ex 1, 2, 10, 3, 4
Jul 26
Lecture 21 The normal distribution
Ch 10.4
Jul 27
Lecture 22 Estimation: bias and variance
Ch 11.1 - 11.2
Quiz 5
Ch 8 and 9.1-9.2
Section 11
Ch 10, Ex 7, 8, 5, 9, Ch 11, Ex 1, 2

Week 7: Regression

Jul 31
Lecture 23 Correlation and the regression line; the regression effect
Ch 11.3 - 11.4
Homework 7
Due Aug 7 at 11:59 PM
Aug 1
Lecture 24 Error in regression
Ch 11.5
Section 12
Ch 11, Ex 3, 4, 9, 11, 10, 7
Aug 2
Lecture 25 Inference in regression
Ch 12.1 - 12.3
Aug 3
Lecture 26 Conclusion
Quiz 6
Ch 10
Section 13
Ch 12, Ex 3, 4

Week 8: Review and Final Exam

Aug 7
Lecture 27 Buffer/Review
Aug 8
Lecture 28 Buffer/Review
Section 14
Practice Problems 10, 21, 22, 25, 18, 14, 13
Aug 9
Lecture 29 Buffer/Review
Aug 10
Final Exam From 10:30 AM - 1:30 PM