Paul Cartledge

Science Instructor, Faculty of Science - Mathematics & Statistical Sciences
Rec Facilities Attendant, Student Services - Athletics Marketing

Fall Term 2021 (1770)

STAT 151 - Introduction to Applied Statistics I

★ 3 (fi 6)(EITHER, 3-0-0)

Data collection and presentation, descriptive statistics. Probability distributions, sampling distributions and the central limit theorem. Point estimation and hypothesis testing. Correlation and regression analysis. Goodness of fit and contingency table. Prerequisite: Mathematics 30-1 or 30-2. Note : This course may not be taken for credit if credit has been obtained in any STAT course, or in KIN 109, PEDS 109, PSYCO 211, SCI 151 or SOC 210.

LECTURE B1 (44510) Download syllabus
2021-09-01 - 2021-12-07
MWF 10:00 - 10:50 (C E1-60)

LECTURE C1 (54360) Download syllabus
2021-09-01 - 2021-12-07
MWF 12:00 - 12:50 (ECHA 2-190)


STAT 235 - Introductory Statistics for Engineering

★ 3 (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; PSYCO 211, SCI 151 or SOC 210. (2) Intended for Engineering students. Other students who take this course will receive *3.0.

LECTURE EA1 (45196) Download syllabus
2021-09-01 - 2021-12-07
TH 08:00 - 09:20 (CCIS L1-140)

Winter Term 2022 (1780)

STAT 151 - Introduction to Applied Statistics I

★ 3 (fi 6)(EITHER, 3-0-0)

Data collection and presentation, descriptive statistics. Probability distributions, sampling distributions and the central limit theorem. Point estimation and hypothesis testing. Correlation and regression analysis. Goodness of fit and contingency table. Prerequisite: Mathematics 30-1 or 30-2. Note : This course may not be taken for credit if credit has been obtained in any STAT course, or in KIN 109, PEDS 109, PSYCO 211, SCI 151 or SOC 210.

LECTURE P1 (76248) Download syllabus
2022-01-05 - 2022-04-08
MWF 08:00 - 08:50 (C E1-60)


STAT 235 - Introductory Statistics for Engineering

★ 3 (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; PSYCO 211, SCI 151 or SOC 210. (2) Intended for Engineering students. Other students who take this course will receive *3.0.

LECTURE EQ1 (72694) Download syllabus
2022-01-05 - 2022-04-08
TH 08:00 - 09:20 (C E1-60)

LECTURE ES1 (72186) Download syllabus
2022-01-05 - 2022-04-08
TH 11:00 - 12:20 (CCIS L2-190)