This is the web page for AMS 131 section 1 (spring 2019). The following abbreviations will be used here:

DD = David Draper (Professor; email address draper@ucsc.edu), LB = Laura Baracaldo (TA; email address lbaracal@ucsc.edu), RG = Rene Gutierrez (TA; email address rgutie17@ucsc.edu), XY = Xingchen (Joe) Yu (TA; email address xyu26@ucsc.edu), BE = Baskin Engineering, E2 = Engineering 2, JL = Jack's Lounge (on the ground floor of BE: it's the big open area with whiteboards, on the opposite end of the building from the coffee place) , and DS = DeGroot and Schervish (the textbook for the class).

The catalog description for AMS 131 is as follows:

Introduction to probability theory and its applications. Combinatorial analysis, axioms of probability and independence, random variables (discrete and continuous), joint probability distributions, properties of expectation, Central Limit Theorem, Law of Large Numbers, Markov chains. Students cannot receive credit for this course and course 203 and Computer Engineering 107. Prerequisite(s): course 11B or Economics 11B or Mathematics 11B or 19B or 20B. (General Education Code(s): Q, SR - Statistical Reasoning)

    • (2 Apr 2019) Announcements will be posted in this section. The first Attachment section below will contain scanned PDF copies of the document camera lecture notes and extra lecture notes, as well as case studies and R code; the second Attachment section will contain secure documents, available only by logging into the web page.
    • (2 Apr 2019) All of the Tue and Thu lectures and the Wed 9.20-10.25am discussion sections will be webcastTo watch a video of one of the lectures or discussion sections, go to webcast.ucsc.edu ; in the third or fourth row down from the top in the Webcast Course List you'll find a row that begins AMS 131 David Draper; in the right-most column of that row under the heading Link, click on Video List; on the page you come to next, in the top yellow box type in the username for this course, which is ams-131-1 ; in the next yellow box type in the password for this course, which is uncertainty-quantification (two character strings linked by dashes, no spaces, all in lower case; this is a long password, but if you make sure that the Remember me box has a check mark in it, you won't have to type in the password from now on, as long as you're using the same computer each time); now click on the blue Login box and you're at the Course Webcasts page. To watch a video just click on it, and then click the relevant symbol on the left just below the video screen: right arrow for watching, left arrow for going back, double vertical line for pause (this is one of the great advantages of webcasts: you can't pause or rewind me in real time in class, but you can pause or rewind the videos as much as you like).
    • (4 Apr 2019) Office hours for this class, starting on Fri 5 Apr 2019, will be as follows (please see the list of abbreviations toward the top of this page):
        Day Time Location Who
        Monday 9-10am BE room 312C/D LB
        Monday noon-1pm BE room 312C/D XY
        Tuesday 9-10am E2 room 586 RG
        Tuesday 7.10-8.40pm E2 room 194 DD
        Wednesday 8-9am BE room 312C/D LB
        Thursday 9-10am E2 room 586 RG
        Thursday 7.10-8.40pm E2 room 194 DD
        Friday 9.30-10.30am BE room 360 XY
    • (8 Apr 2019) You can get free tutoring (Modified Supplemental Instruction (MSI)) for this course through Learning Support Services (LSS): our tutor for this class is Michael Beneschan (email address mbenesch@ucsc.edu). The tutoring schedule is as follows (tutoring starts on Mon 8 Apr 2019):
        Day Time Location
        Monday 10.30-11.30am Porter 246
        Monday 4-5pm ARCenter 116
        Tuesday 10-11am Oakes Learning Center
        Wednesday 1.20-2.20pm ARCenter 221
        Wednesday 2.30-3.40pm ARCenter 203
        Thursday 10-11am Crown 104
      The schedule is also available at https://lss.ucsc.edu/programs/modified-supplemental-instruction/msi-schedule.html . To get tutoring help for this class, just show up at one of the times and places listed above and Michael will help everybody who's there.
    • (8 Apr 2019) Our official note-takers this quarter are Emmanuel Garcia Vizcarra (EGV below) and Barbara Haggerty (BH below); their notes from the document camera will be posted along with mine.
    • (9 Apr 2019) The discussion sections for the class are as follows:
        Day Time Location Presenter
        Wednesday 9.20-10.25am Earth & Marine B214 DD
        Wednesday 10.40-11.45am Earth & Marine B214 RG
        Wednesday 2.40-3.45pm Earth & Marine B214 LB
        Friday noon-1.05pm Earth & Marine B214 RG
        Friday 1.20-2.25pm Earth & Marine B214 XY
        Friday 2.40-3.45pm Earth & Marine B214 XY
    • (24 Apr 2019) A cautionary taleClick here to read a New York Times article documenting three alarming examples in which bad data science was used to wrongfully convict people of serious crimes. The depressingly familiar moral of this story is that just because an "expert" says the odds are 1 in a million against anyone other than defendant X having committed the crime doesn't mean that this uncertainty assessment is accurate.
    • (14 May 2019) Please note the important change in time and place for DD's office 1.5-hours: starting on 14 May 2019 and for the rest of the quarter, they will be from 7.10pm to 8.40pm in E2 room 194.
AttachmentSize
PDF icon Document camera notes (lecture: 2 Apr 2019) (random samples from populations; IID and SRS; equally-likely model)147.65 KB
PDF icon Note-taker notes, EGV (lecture: 2 Apr 2019)3 MB
PDF icon Note-taker notes, BH (lecture: 2 Apr 2019)3.49 MB
PDF icon Quiz 1 in PDF format (due at canvas.ucsc.edu by 11.59pm on Fri 12 Apr 201937.08 KB
Plain text icon Quiz 1 in LaTeX format (due at canvas.ucsc.edu by 11.59pm on Fri 12 Apr 20192.12 KB
PDF icon Document camera notes (discussion section: 3 Apr 2019) (solving problems from DS chapter 1)199.96 KB
PDF icon Note-taker notes, BH (discussion section: 3 Apr 2019)2.54 MB
PDF icon Document camera notes (lecture: 4 Apr 2019) (probability rules for AND, OR, NOT and GIVEN; mutually exclusive; independence)303.44 KB
PDF icon Note-taker notes, EGV (lecture: 4 Apr 2019)3.86 MB
PDF icon Note-taker notes, BH (lecture: 4 Apr 2019)3.78 MB
PDF icon Extra notes (lecture: 4 Apr 2019) (experiment, event, sample space, set theory, cardinality, infinite sets)234.39 KB
PDF icon Case studies: (1) Dr. Schram and (2) Fisher's constitutional hypothesis126.93 KB
PDF icon Take-Home Test 1 in PDF format (current target due date: uploaded to canvas.ucsc.edu by 11.59pm on Sun 28 Apr 2019) 174.67 KB
Plain text icon Take-Home Test 1 in LaTeX format (current target due date: uploaded to canvas.ucsc.edu by 11.59pm on Sun 28 Apr 2019) 26.64 KB
PDF icon Tentative syllabus and reading list for the course67.14 KB
PDF icon Quiz 2 in PDF format (due at canvas.ucsc.edu by 11.59pm on Tue 16 Apr 201981.03 KB
Plain text icon Quiz 2 in LaTeX format (due at canvas.ucsc.edu by 11.59pm on Tue 16 Apr 20191.91 KB
PDF icon Case study: roulette64.25 KB
Plain text icon R code for simulating roulette1.44 KB
PDF icon Document camera notes (lecture: 9 Apr 2019) (solution to Dr. Schram and Fisher case studies; scatterplot; positive association)215.15 KB
PDF icon Extra notes (lecture: 9 Apr 2019) (orders of infinity, more set theory, partitions, Kolmogorov probability axioms)234.39 KB
PDF icon Note-taker notes, EGV (lecture: 9 Apr 2019)1.96 MB
PDF icon Note-taker notes, BH (lecture: 9 Apr 2019)7.19 MB
PDF icon Document camera notes (discussion section: 10 Apr 2019) (using Monte-Carlo simulation to analyze roulette)80.33 KB
PDF icon Note-taker notes, BH (discussion section: 10 Apr 2019)862.95 KB
PDF icon Document camera notes (lecture: 11 Apr 2019) (causality; Bayes's Theorem (probability, odds); Monte Hall, Cromwell)377.82 KB
PDF icon Extra notes (lecture: 11 Apr 2019) (consequences of Kolmogorov axioms; permutations)252.03 KB
PDF icon Note-taker notes, EGV (lecture: 11 Apr 2019)2.23 MB
PDF icon Note-taker notes, BH (lecture: 11 Apr 2019)4.51 MB
PDF icon Case studies: Monte Hall and Cromwell's Rule178.12 KB
Plain text icon R code to solve the birthday problem7.14 KB
Plain text icon R code to simulate the matching problem2.07 KB
PDF icon Quiz 3 in PDF format (due at canvas.ucsc.edu by 11.59pm on Tue 23 Apr 201958.57 KB
Plain text icon Quiz 3 in LaTeX format (due at canvas.ucsc.edu by 11.59pm on Tue 23 Apr 20193.1 KB
PDF icon Document camera notes (lecture: 16 Apr 2019) (death penalty case study, Simpson's Paradox)225.45 KB
PDF icon Note-taker notes, EGV (lecture: 16 Apr 2019)2.45 MB
PDF icon Note-taker notes, BH (lecture: 16 Apr 2019)4.53 MB
PDF icon Extra notes (lecture: 16 Apr 2019) (combinations; birthday problem; binomial and multinomial coefficients)416.7 KB
PDF icon Case study: imposition of the death penalty54.99 KB
PDF icon Document camera notes (discussion section: 17 Apr 2019) (ELISA screening for HIV)105.21 KB
PDF icon Note-taker notes, BH (discussion section: 17 Apr 2019)931.94 KB
PDF icon Case study: ELISA screening for HIV108.64 KB
PDF icon Document camera notes (lecture: 18 Apr 2019) (credit-card screening case study; simulation estimates of probabilities)137.44 KB
PDF icon Extra notes (lecture: 18 Apr 2019) (matching problem; conditional probability: definition and results; Law of Total Probability)263.25 KB
PDF icon Case study: credit card screening66.27 KB
PDF icon Note-taker notes, EGV (lecture: 18 Apr 2019)2.71 MB
PDF icon Note-taker notes, BH (lecture: 18 Apr 2019)3.65 MB
PDF icon Quiz 4 in PDF format (due at canvas.ucsc.edu by 11.59pm on Tue 30 Apr 201991.89 KB
Plain text icon Quiz 4 in LaTeX format (due at canvas.ucsc.edu by 11.59pm on Tue 30 Apr 20193.94 KB
PDF icon Document camera notes (lecture: 23 Apr 2019) (Bayes's Theorem in odds form, and directly by partitioning)228.21 KB
PDF icon Extra notes (lecture: 23 Apr 2019) (unconditional and conditional independence; discrete and continuous random variables; PMFs)415.96 KB
PDF icon Note-taker notes, EGV (lecture: 23 Apr 2019)3.73 MB
PDF icon Note-taker notes, BH (lecture: 23 Apr 2019)5.72 MB
PDF icon Document camera notes (discussion section: 24 Apr 2019) (exploring the family of Binomial distributions)54.32 KB
Plain text icon R code to explore the Binomial and Poisson distributions8.43 KB
PDF icon Note-taker notes, BH (discussion section: 24 Apr 2019)581.23 KB
PDF icon Document camera notes (lecture: 25 Apr 2019) (Meaning of probability density functions)78.1 KB
PDF icon Extra notes, part 1 (lecture: 25 Apr 2019) (Poisson distribution, Poisson Process)221.96 KB
PDF icon Extra notes, part 2 (lecture: 25 Apr 2019) (Histograms, Bernoulli and Uniform discrete distributions; PDFs for continuous RVs)370.91 KB
PDF icon Note-taker notes, EGV (lecture: 25 Apr 2019)2.79 MB
PDF icon Note-taker notes, BH (lecture: 25 Apr 2019)6.01 MB
PDF icon Quiz 5 in PDF format (due at canvas.ucsc.edu by 11.59pm on Tue 7 May 201978.67 KB
Plain text icon Quiz 5 in LaTeX format (due at canvas.ucsc.edu by 11.59pm on Tue 7 May 20191.84 KB
PDF icon Document camera notes (lecture: 30 Apr 2019) (Distributional shapes, calculations with PDFs and CDFs)342.31 KB
PDF icon Extra notes (lecture: 30 Apr 2019) (mixed (discrete-continuous) distributions; cumulative distribution functions (CDFs))302.86 KB
PDF icon Note-taker notes, EGV (lecture: 30 Apr 2019)2.24 MB
PDF icon Note-taker notes, BH (lecture: 30 Apr 2019)4.32 MB
PDF icon Document camera notes (discussion section: 1 May 2019) (PMFs, PDFs, CDFs and inverse CDFs: Binomial, Exponential distributions)105.81 KB
PDF icon Note-taker notes, BH (discussion section: 1 May 2019)1.2 MB
Plain text icon R code to explore PMFs, CDFs, PDFs and inverse CDFs in the Binomial and Exponential families of distributions)2.59 KB
Plain text icon R code to visualize the bivariate densities on pages 98 and 113 of the extra notes3.35 KB
PDF icon Document camera notes (lecture: 2 May 2019) (Calculations with joint continuous PDFs)63.76 KB
PDF icon Extra notes (lecture: 2 May 2019) (Inverse CDF (quantile function), median, interquartile range; bivariate joint distributions)415.17 KB
PDF icon Note-taker notes, EGV (lecture: 2 May 2019)1.46 MB
PDF icon Note-taker notes, BH (lecture: 2 May 2019)3.21 MB
PDF icon Take-Home Test 2 in PDF format (current target due date: uploaded to canvas.ucsc.edu by 11.59pm on Sun 19 May 2019) 176.57 KB
Plain text icon Take-Home Test 2 in LaTeX format (current target due date: uploaded to canvas.ucsc.edu by 11.59pm on Sun 19 May 2019) 17.46 KB
PDF icon Quiz 6 in PDF format (due at canvas.ucsc.edu by 11.59pm on Fri 17 May 2019)85.18 KB
Plain text icon Quiz 6 in LaTeX format (due at canvas.ucsc.edu by 11.59pm on Fri 17 May 2019)1.9 KB
PDF icon Document camera notes (lecture: 7 May 2019) (Joint, marginal and conditional distributions)34.87 KB
PDF icon Extra notes (lecture: 7 May 2019) (Bivariate CDFs and PDFs; marginal and conditional distributions; nuts and bolts case study)593.5 KB
PDF icon Note-taker notes, EGV (lecture: 7 May 2019)1.21 MB
PDF icon Note-taker notes, BH (lecture: 7 May 2019)6.91 MB
PDF icon Document camera notes (lecture: 9 May 2019) (Transformations of a univariate random variable)104.51 KB
PDF icon Extra notes (lecture: 9 May 2019) (Multivariate distributions; multivariate LTP and Bayes's Theorem; univariate transformations)572.87 KB
PDF icon Note-taker notes, BH (lecture: 9 May 2019)8.49 MB
PDF icon Document camera notes (lecture: 14 May 2019) (Properties of expected value of a random variable)71.06 KB
PDF icon Extra notes (lecture: 14 May 2019) (Transformations of functions of 2 or more random variables; expected value)886.92 KB
PDF icon Note-taker notes, EGV (lecture: 14 May 2019)1.67 MB
PDF icon Note-taker notes, BH (lecture: 14 May 2019)6.77 MB
PDF icon Document camera notes (discussion section: 15 May 2019) (Expected value for Binomial and Poisson distributions)174.76 KB
PDF icon Note-taker notes, BH (discussion section: 15 May 2019)945.26 KB
PDF icon Quiz 7 in PDF format (due at canvas.ucsc.edu by 11.59pm on Fri 24 May 2019)63.16 KB
Plain text icon Quiz 7 in LaTeX format (due at canvas.ucsc.edu by 11.59pm on Fri 24 May 2019)2.03 KB
Plain text icon R code to illustrate the use of the Probability Integral Transform to generate pseudo-random draws from a given PDF651 bytes
PDF icon Document camera notes (lecture: 16 May 2019) (Properties of variances and standard deviations)190.07 KB
PDF icon Extra notes (lecture: 16 May 2019) (Expected value. variance, standard deviation, moments, moment generating function)638.84 KB
PDF icon Note-taker notes, EGV (lecture: 16 May 2019)966.53 KB
PDF icon Note-taker notes, BH (lecture: 16 May 2019)4.03 MB
PDF icon Document camera notes (lecture: 21 May 2019) (Root mean squared prediction error; properties of correlation)187.85 KB
PDF icon Extra notes (lecture: 21 May 2019) (Moment-generating functions; prediction; covariance and correlation)716.99 KB
PDF icon Note-taker notes, EGV (lecture: 21 May 2019)2.16 MB
PDF icon Note-taker notes, BH (lecture: 21 May 2019)4.16 MB
PDF icon Document camera notes (discussion section: 22 May 2019) (Variance, covariance and correlation calculations in two DS problems)157.42 KB
PDF icon Note-taker notes, BH (discussion section: 22 May 2019)1.17 MB
PDF icon Quiz 8 in PDF format (due at canvas.ucsc.edu by 11.59pm on Fri 31 May 2019)64.61 KB
Plain text icon Quiz 8 in LaTeX format (due at canvas.ucsc.edu by 11.59pm on Fri 31 May 2019)2.13 KB
PDF icon Document camera notes (lecture: 23 May 2019) (Correlation; utility)200.66 KB
PDF icon Extra notes (lecture: 23 May 2019) (Continuous LTP; Double-Expectation Theorem; conditional variance; utility; MEU)552.15 KB
PDF icon Note-taker notes, EGV (lecture: 23 May 2019)1.33 MB
PDF icon Note-taker notes, BH (lecture: 23 May 2019)5.71 MB
PDF icon Take-Home Test 3 in PDF format (absolute due date: uploaded to canvas.ucsc.edu by 11.59pm on Sun 16 Jun 2019) 199.12 KB
Plain text icon Take-Home Test 3 in LaTeX format (absolute due date: uploaded to canvas.ucsc.edu by 11.59pm on Sun 16 Jun 2019) 22.3 KB
PDF icon Document camera notes (lecture: 28 May 2019) (Normal distribution; converting to standard units)73.3 KB
PDF icon Extra notes (lecture: 28 May 2019) (Binomial, Hypergeometric, Poisson, Negative Binomial, Geometric, Normal distributions)821.6 KB
PDF icon Note-taker notes, EGV (lecture: 28 May 2019)2 MB
PDF icon Note-taker notes, BH (lecture: 28 May 2019)15.05 MB
PDF icon Document camera notes (discussion section: 29 May 2019) (Probability vs. statistical inference; London Underground case study)107.84 KB
PDF icon Note-taker notes, BH (discussion section: 29 May 2019)921.29 KB
PDF icon Case study: the London Underground148.79 KB
Plain text icon R code for the London Underground case study4.27 KB
PDF icon Document camera notes (lecture: 30 May 2019) (Bivariate Normal distribution)86.34 KB
PDF icon Extra notes (lecture: 30 May 2019) (Lognormal, Gamma, Exponential, Beta, Multinomial, Bivariate Normal distributions)1.05 MB
PDF icon Note-taker notes, BH (lecture: 30 May 2019)6.88 MB
PDF icon Quiz 9 in PDF format (due at canvas.ucsc.edu by 11.59pm on Fri 7 Jun 2019)106.85 KB
Plain text icon Quiz 9 in LaTeX format (due at canvas.ucsc.edu by 11.59pm on Fri 7 Jun 2019)4.54 KB
Plain text icon R code to explore the Geometric, Negative Binomial, Gamma, Beta and Bivariate Normal distributions8.87 KB
Plain text icon R code for exploring Markov chains10.04 KB
PDF icon Quiz 10 in PDF format (due at canvas.ucsc.edu by 11.59pm on Fri 14 Jun 2019)79.3 KB
Plain text icon Quiz 10 in LaTeX format (due at canvas.ucsc.edu by 11.59pm on Fri 14 Jun 2019)3.9 KB
PDF icon Document camera notes (lecture: 4 Jun 2019) (Propagation of error)58.15 KB
PDF icon Extra notes (lecture: 4 Jun 2019) (Chebyshev's inequality, WLLN, Central Limit Theorem, Delta Method)574.96 KB
PDF icon Note-taker notes, EGV (lecture: 4 Jun 2019)2.06 MB
PDF icon Note-taker notes, BH (lecture: 4 Jun 2019)10.82 MB
PDF icon Extra notes (lecture: 5 Jun 2019) (Markov chains, 1-step transition matrix, random walk, equilibrium distribution)810.77 KB
PDF icon Document camera notes (lecture: 6 Jun 2019) (Confidence intervals; t distribution; statistical significance)482.48 KB