Teaching
This section is divided into three segments describing the courses for which tutoring is offered: Introduction to Statistics, Analysis of Variance (ANOVA), and related courses. In each segment you will find a description of the course, a list of courses that fit that description, and some recommended readings.
Teaching method
The teaching method entails an individual approach, where the educator teaches the material according to the students’ interests using examples they can relate to. This makes the learning experience interesting and more enjoyable. The motto is « stats don’t suck », meaning statistics can be fun to learn and use!
« … teaching and learning are not possible without the search … and without joy. »
Paulo Freire
Teaching strategy
Individual tutoring is available subject to schedule availability. Another option is to set small groups of 3 or 4 students. This helps build a more enjoyable learning environment and students benefit from others’ questions. Students are matched based on their interests, skills, and personalities to ensure the group is cohesive.
Review and Problem Solving sessions are organized before midterms and final exams. Sessions are held separately for the Introduction to Statistics and the Analysis of Variance (ANOVA) students. These sessions cover the entire content being assessed and are held for classes with large number of students due to a higher demand for tutoring during those periods. Contact me to register for the next Review and Problem Solving sessions.
Course pack
Original course packs for Introduction to Statistics and Analysis of Variance (ANOVA) can be purchased upon order. The course packs focus on the most important material in the courses, yet are general enough to fit the needs of different students. Partially filled out versions are available for students who want to complete the course pack as they learn the material. Contact me to order.
Introduction to Statistics is the first statistics courses all undergraduate students must take. The Introduction to Statistics course offered in different departments and universities cover similar topics. This course starts with elementary statistics, such as frequency distribution, average, standard deviation, and variance. It goes through correlation, regression, and probability. And it ends with z-score, normal curve, sampling distribution, hypothesis testing, t-test, f-test, and chi-square.
This course is a prerequisite for most statistics courses.
Contact me to schedule an Introduction to Statistics tutoring session.
List of Courses
At McGill University:
PSYC 204 – Introduction to Statistics
SOCI 350 – Statistics in Social Research
MATH 323 – Probability
MATH 324 – Statistics
MATH 357 – Honours Statistics
and others.
At Concordia University:
PYSC 315 – Statistical Analysis I
and others.
Recommended Readings
Amsel, R. (n.d.). PSYC 204: Introduction to statistics [course pack].
Ferguson, G. A. & Takane, Y. (1989). Statistical analysis in psychology and education (6th ed.).
New York: McGraw Hill.
Gravetter, F. J. & Wallnau, L. B. (2008). Essentials of statistics for the behavioural sciences (8th
ed.). Belmont, CA: Wadsworth.
Olsen, Chester L. (1987). Making sense of data. Dubuque, IA: WC Brown.
ANOVA is an acronym for Analysis of Variance and is usually taught in the second statistics course offered at the undergraduate level. The course’s title varies between departments and universities, but its contents are essentially the same. The course focuses on one-, two-, and three-way ANOVAs; independent, repeated, and mixed measures; and post-hoc tests, planned comparisons and orthogonal tests. Occasionally professors extend the course content to include nonparametric tests, multiple regression, and Analysis of Covariance (ANCOVA).
Contact me to schedule an ANOVA tutoring session.
List of Courses
At McGill University:
PSYC 305 – Statistics for Experimental Design
MATH 423 – Regression and Analysis of Variance
MATH 533 – Honours Regression and Analysis of Variance and others.
At Concordia University:
PYSC 316 – Statistical Analysis II
and others.
Recommended Readings
Amsel, R. (n.d.). PSYC 305: Statistics for experimental design [course pack].
Ferguson, G.A. & Takane, Y. (1989). Statistical analysis in psychology and education (6th ed.).
New York: McGraw Hill.
Olsen, Chester L. (1987). Making sense of data. Dubuque, IA: WC Brown.
Many related courses that teach statistical procedures for research are offered at the undergraduate and graduate levels. These courses encompass topics specific to departments or graduate theses. These courses include:
EDPE 575 – Educational Measurement
EDPE 675 – Intermediate Statistics 1
EDPE 676 – Intermediate Statistics 2
EDPE 682 – Univariate/Multivariate Analysis
MGCR 271 – Business Statistics
MATH 204 – Principles of Statistics
MATH 523 – Generalized Linear Model
MATH 524 – Nonparametric tests
and others.
Students interested in tutoring sessions for these courses should have separate sessions from the Introduction to Stats and the ANOVA students. The teaching method will entail an individual approach, adapted to the area of expertise of each student. The teaching strategy will be developed case by case.
Contact me to schedule a tutoring session.
