Math 203: Principles of Statistics 1

Fall 2024

Instructors

Section 001

David A. Stephens (david.stephens@mcgill.ca, Burnside 1225)

   

Section 002

José A. Correa (jose.a.correa@mcgill.ca, Burnside 1233)

   

Textbook

Statistics (13th Edition)

J.T. McClave and T. Sincich

   

Purchasing the textbook is not mandatory; the course will follow the structure of Chapters 1–9, but the course materials will be self-contained.

Method of Evaluation: Evaluation for the course will be on the following basis

Please see the Course Schedule for the timing of the in-term assessments.

Note: The final grade will be determined by the aggregate score

70%  Final E xam + 18 % A ssig nm ents + 12 % Q uizzes

if this score exceeds the principal method of evaluation.

Target Course Schedule








Wk

Date

Lectures

Topics

Q

A







1

26/08

1–2

Outline & General Information. Introduction. Elements of Statistical Analysis







2

02/09

3–4

Types of Data. Data Collection. Designed and Observational Studies. Descriptive Methods Simpson’s Paradox. Graphical Methods: Histograms







3

09/09

5–7

Graphical Methods: Histograms & interpretation. Measures of Centre. Measures of Spread

Q1







4

16/09

8–10

Describing Quantitative Data. The Empirical Rule. Chebychev‘s Rule. Z-scores Graphical Methods: Boxplots

Q2

A1







5

23/08

11–13

Probability: Uncertainty. Set theory, operations and Venn Diagrams. Sample spaces & Events. Mutually Exclusive Events. Partitions. De Morgan’s Laws. Probability rules.

Q3







6

30/09

14–16

Conditional Probability. Independence, Theorem of Total Probability. Bayes Theorem.

Q4







7

07/10

17–18

Discrete Random Variables. Expectation & Variance. Discrete Uniform, Bernoulli, binomial, geometric, Poisson distributions.

Q5

A2







8

14/10

-

Fall Reading Break

-

-







9

21/10

19–21

Cumulative Probability. Continuous Distributions. Normal Distribution. Sampling Distributions. Sample Mean as a Random Variable

Q6







10

28/10

22–24

Central Limit Theorem. Point Estimation (μ and p). Interval Estimation: The t distribution.

Q7

A3







11

04/11

25–27

Inference for one sample: Interval Estimators, Confidence Intervals, Examples The Assumption of Normality. Q-Q Plots. Hypothesis Testing: Hypotheses Set-up. Type 1 and 2 Errors.

Q8







12

11/11

28–30

Hypothesis Testing: Test Statistic Rejection Region. Scenarios Test Statistic Rejection Region. Examples. p-values. Motivation. Interpretation.

Q9

A4







13

18/11

31–33

Inference for two samples. Confidence Intervals. Examples. Hypothesis testing for two samples.







14

25/11

34–36

Inference & Hypothesis testing for two samples: Scenarios and Examples







15

02/12

37–38

Course Review
Exam preparation








Policy on Late Submission:

Key Academic Dates: https://www.mcgill.ca/importantdates/key-dates

Tutorials & Office Hours:

Scheduling details will be announced shortly.

myCourses:

David A. Stephens & José A. Correa

Department of Mathematics and Statistics

McGill University

August 27, 2024

McGill Policy Statements