Sharandeep Pandher

Assistant Lecturer, Faculty of Science - Mathematics & Statistical Sciences
Directory

Summer Term 2024 (1880)

STAT 235B - Introductory Statistics for Engineering

1.5 units (fi 6)(EITH/SP/SU, 3-0-1.5)

Descriptive data analysis. Calculus of Probability. Binomial, multinomial, Poisson, normal, beta, exponential, gamma, hypergeometric, and Weibull distributions. Sampling distributions. Estimation, testing hypotheses, goodness-of-fit tests, and one-way analysis of variance. Linear correlation and regression. Sampling. Quality control. Use of a microcomputer software package for statistical analyses in engineering applications. Prerequisite: MATH 100. Corequisite: MATH 101. Notes: (1) This course may not be taken for credit if credit has already been obtained in one of STAT 141, 151, 222, 265, 266; PSYCH 211, SCI 151 or SOC 210. (2) Intended for Engineering students. Other students who take this course will receive *3.0.

LECTURE C1 (40068)

2024-07-01 - 2024-08-02
MWF 11:00 - 11:50

Fall Term 2024 (1890)

SCI 201 - The Scientific Process

3 units (fi 6)(EITHER, 3-1S-0)

This course addresses qualities of competent scientists, research ethics, the multidisciplinary approach to studies in the natural and social sciences, and types of scientific studies. As part of the course, students conduct mini-research projects to practice working through all four phases of the scientific process: planning and preparation, data collection, data analysis and interpretation, and scientific writing and presentation. Prerequisites: A minimum of C- in STAT 151 or STAT 161 and any 100-level science course.

SEMINAR E1 (54959)

2024-09-03 - 2024-12-09
T 15:30 - 16:20

SEMINAR E2 (54960)

2024-09-03 - 2024-12-09
R 12:30 - 13:20



STAT 235 - Introductory Statistics for Engineering

3 units (fi 6)(EITH/SP/SU, 3-0-1.5)

Descriptive data analysis. Calculus of Probability. Binomial, multinomial, Poisson, normal, beta, exponential, gamma, hypergeometric, and Weibull distributions. Sampling distributions. Estimation, testing hypotheses, goodness-of-fit tests, and one-way analysis of variance. Linear correlation and regression. Sampling. Quality control. Use of a microcomputer software package for statistical analyses in engineering applications. Prerequisite: MATH 100. Corequisite: MATH 101. Notes: (1) This course may not be taken for credit if credit has already been obtained in one of STAT 151, 161, 222, 265, 266, 276, 281; KIN 109, PEDS 109, PSYCH 211, PTHER 352, SCI 151 or SOC 210. (2) Intended for Engineering students. (2) Intended for Engineering students. Other students who take this course will receive 3.0 units.

LECTURE EC1 (55067)

2024-09-03 - 2024-12-09
TR 08:00 - 09:20



STAT 378 - Applied Regression Analysis

3 units (fi 6)(EITHER, 3-0-0)

Simple linear regression analysis, inference on regression parameters, residual analysis, prediction intervals, weighted least squares. Multiple regression analysis, inference about regression parameters, multicollinearity and its effects, indicator variables, selection of independent variables. Non-linear regression. Prerequisite: One of STAT 266 or STAT 276, or STAT 235 with consent of the Department.

LECTURE A1 (47540)

2024-09-03 - 2024-12-09
MWF 10:00 - 10:50



STAT 437 - Applied Statistical Methods

3 units (fi 6)(EITHER, 3-0-0)

Methods of data analysis useful in applied research, including repeated measures and longitudinal data analysis, non-linear regression, survival analysis, multivariate techniques. Applications to real data will be emphasized, including case studies and real data applications. Each researcher works on a project to present, highlighting the methods used in the project. Prerequisite: STAT 252 or 337 or consent of the instructor.

LECTURE A1 (50267)

2024-09-03 - 2024-12-09
MWF 09:00 - 09:50