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