Course Details 1. Introduction to Probabilities
Course Outline

Initial meeting: 12-jan (37:44)

Instructor: Patrick Boily, uOttawa
Communications with the Instructor must be conducted through Slack. The Slack invite link is available in the “Announcements” section on Brigthspace.

Exercise Sessions Schedule:
    Tuesdays, 10:00-11:20, Jan 12 – Apr 13
    Thursdays, 08:30-09:50, Jan 14 – Apr 08
    No session on Feb 16 and Feb 18

Exercise Sessions Zoom link

Important Dates:
    Feb 4: assignment 1 due
    Feb 25: midterm examination
    Mar 16: assignment 2 due
    Apr 8: assignment 3 due

Note: the assignments must be uploaded as a single PDF document to Brightspace.

Mobius Exam Instructions (VERY IMPORTANT!!! you must purchase a license [you may already have one] before the midterm exam. Note that the price of the license is much lower than that of the non-mandatory textbook.) Further instructions have been posted on Slack on Feb 9.

Statistics Help Centre

Slide Deck

Video Lectures: (2:52:22)
    12-Jan: 1.1 Sample Spaces and Events (14:29)
    12-Jan: 1.2 Counting Techniques (12:15)
    12-Jan: 1.3 Ordered Samples (16:19)
    14-Jan: 1.4 Unordered Samples (11:27)
    14-Jan: 1.5 Probability of an Event (29:25)
    19-Jan: 1.6 Conditional Prob. & Indep. Events (52:44)
    21-Jan: 1.7 Bayes’ Theorem (35:43)

Exercises: Q1-Q30, Q61, Q71-Q72


Important Documents:
    Practice Set (in-class exercises)
    Additional Questions with Answers
    Midterm Exam – 2020 (provided as an example only)

Assignments and Midterm:
    Assignment 1 (due 04-Feb, 3:00PM EST) – Solutions
    Assignment 2 (due 16-Mar, 3:00PM EST)
    Assignment 3 (coming soon)
    Midterm Solutions

Some of the video lectures (from 2-2 onwards) are available without a soundtrack here.

2. Discrete Random Variables 3. Continuous Random Variables
Slide Deck

Video Lectures: (1:33:32)
    26-Jan: 2.1 Random Variables and Distributions (27:36)
    26-Jan: 2.2 Expectation of a Discrete R.V. (23:28)
    28-Jan: 2.3 Binomial Distributions (19:40)
    28-Jan: 2.4 Geometric Distributions (03:20)
    28-Jan: 2.5 Negative Binomial Distributions (05:25)
    02-Feb: 2.6 Poisson Distributions (14:03)

Exercises: Q31-Q46, Q54-Q57, Q59, Q64, Q69-Q70, Q74, Q77-Q78

Slide Deck

Video Lectures: (2:10:37)
    02-Feb: 3.1 Probability Density Functions (36:23)
    04-Feb: 3.2 Expectation of a Continuous R.V. (08:05)
    04-Feb: 3.3 Normal Distributions (25:48)
    09-Feb: 3.4 Exponential Distributions (11:39)
    09-Feb: 3.5 Gamma Distributions (08:44)
    11-Feb: 3.6 Joint Distributions (32:44)
    11-Feb: 3.7 Normal Approx. of the Binomial Dist. (07:14)

Exercises: Q47-Q53, Q58, Q60, Q62-Q63, Q65-Q67, Q73, Q75

4. Descriptive Statistics and Sampling Distributions 5. Point and Interval Estimation
Slide Deck

Video Lectures: (2:24:42)
    02-Mar: 4.1 Data Descriptions (38:43)
    04-Mar: 4.2 Visual Summaries (17:57)
    09-Mar: 4.3 Sampling Distributions (24:32)
    11-Mar: 4.4 Central Limit Theorem (34:49)
    16-Mar: 4.5 Sampling Distributions (Reprise) (28:41)

Exercises: Q76, Q79-Q92, Q125, Q128, Q136

Slide Deck

Video Lectures: (1:17:26)
    18-Mar 5.1 Statistical Inference (15:29)
    18-Mar 5.2 C.I. for the Mean with Known Variance (32:48)
    23-Mar 5.3 Choice of Sample Size (08:53)
    23-Mar 5.4 C.I. for the Mean with Unknown Variance (11:46)
    23-Mar 5.5 C.I. for a Proportion (08:30)

Exercises: Q93-Q101, Q126-Q127

6. Hypothesis Testing 7. Linear Regression and Correlation
Slide Deck

Video Lectures: (2:09:07)
    25-Mar: 6.0 Claims and Suspicions (20:15)
    25-Mar: 6.1 Hypothesis Testing (07:54)
    25-Mar: 6.2 Null and Alternative Hypotheses (05:58)
    30-Mar: 6.3 Test Statistics and Critical Regions (13:29)
    30-Mar: 6.4 Test for a Mean with Known Variance (34:13)
    01-Apr: 6.5 Test for a Mean with Unknown Variance (06:44)
    01-Apr: 6.6 Test for a Proportion (03:38)
    01-Apr: 6.7 Paired Two-Sample Test (11:56)
    01-Apr: 6.8 Unpaired Two-Sample Test (20:44)
    01-Apr: 6.9 Difference of Two Proportions (04:16)

Exercises: Q102-Q124, Q129-Q130

Slide Deck

Video Lectures: (1:28:44)
    06-Apr: 7.0 Motivating Example (03:17)
    06-Apr: 7.1 Coefficient of Correlation (09:19)
    06-Apr: 7.2 Simple Linear Regression (35:49)
    08-Apr: 7.3 Hypothesis Testing for Linear Regression (11:13)
    08-Apr: 7.4 C.I. and P.I. for Linear Regression (17:06)
    08-Apr: 7.5 Analysis of Variance (08:02)
    08-Apr: 7.6 Coefficient of Determination (03:58)

Exercises: Q131-Q132, Q137-Q148

Exercise Sessions Optional Material
    14-Jan: 1, 2, 3, 4, 5, 6, 7 (1:13:50)
    19-Jan: 8, 9, 10, 11 (0:55:03); 12, 13 [PDF]
    21-Jan: 14, 15, 16, 18, 19 (1:06:10); 17 [PDF]
    26-Jan: 20, 21, 22, 24 (1:00:05); 23, 25, 26 [PDF]
    28-Jan: 27, 28, 29, 30, 61, 71 (0:50:21)
    02-Feb: 31, 32, 33, 34 (0:50:20); 72, 35 [PDF]
    04-Feb: 36, 37, 38, 40, 41, 42 (0:39:52); 36, 39 [PDF]
    09-Feb: 43, 44, 45, 46, 54, 55 (47:11)
    11-Feb: 56, 57, 59, 64, 69, 70 (47:34)
    23-Feb: 50, 74, 47, 48, 49 (48:11)
    02-Mar: Midterm Solutions (no video today)
    04-Mar: 51, 52, 53, 58, 60, 62 (39:54)
    09-Mar: 63, 65, 66, 67, 73, 75 (00:00)
    11-Mar: 76, 79, 80, 81, 82, 83, 84 (00:00)
    16-Mar: 85, 86, 87, 88, 89, 90 (00:00)
    18-Mar: 91, 92, 125, 128, 136 (00:00)
    23-Mar: 93, 94, 95, 96, 97, 98, 99 (00:00)
    25-Mar: 102, 103, 100, 101, 126, 127 (00:00)
    30-Mar: 104, 105, 106, 107, 108 (00:00)
    01-Apr: 114, 115, 116, 117 (00:00)
    06-Apr: 118, 119, 120, 121, 122, 123, 124, 129 (00:00)
    08-Apr: 130, 131, 132, 137, 138, 139, 140 (00:00)
    13-Apr: 141, 142, 143, 144, 145, 146, 147, 148 (00:00)

Statistical Process Monitoring Slide Deck

Video Lectures: (0:43:49)
    8.1 Motivation (02:56)
    8.2 Time Series (08:23)
    8.3 Control Charts (32:30)

Exercises: Q133-135, Q149-Q150

Data Analysis in R Videos: (3:02:26)
    R.1 Basics of R, part 1 (29:50)
    R.2 Basics of R, part 2 (25:01)
    R.3 Random Variables and Distributions (18:08)
    R.4 Descriptive Statistics (05:19)
    R.5 Graphics with ggplot2, part 1 (19:32)
    R.6 Graphics with ggplot2, part 2 (27:03)
    R.7 Central Limit Theorem (12:02)
    R.8 Confidence Intervals (14:10)
    R.9 Hypothesis Testing (16:13)
    R.10 Simple Linear Regression (15:08)