Paul Cartledge

ATS Associate Lecturer, Faculty of Science - Mathematics & Statistical Sciences
Directory

Summer Term 2024 (1880)

STAT 151 - Introduction to Applied Statistics I

3 units (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, PSYCH 211, SCI 151 or SOC 210.

LECTURE B1 (40047)

2024-07-08 - 2024-08-14
MTWRF 13:00 - 14:10

Fall Term 2024 (1890)

STAT 151 - Introduction to Applied Statistics I

3 units (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. Notes: (1) Credit can be obtained in at most one of STAT 151, STAT 161, and STAT 235. (2) This course may not be taken for credit if credit has been obtained in STAT 222, STAT 266, STAT 276, KIN 109, PEDS 109, PSYCH 211, PTHER 352, SCI 151 or SOC 210.

LECTURE F1 (47537)

2024-09-03 - 2024-12-09
TR 12:30 - 13:50



STAT 161 - Introductory Statistics for Business and Economics

3 units (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. Use of a microcomputer software package for statistical analyses in business and economics. Prerequisite: Mathematics 30-1 or 30-2. Notes: (1) Credit can be obtained in at most one of STAT 151, STAT 161, and STAT 235. (2) This course may not be taken for credit if credit has been obtained in obtained in STAT 222, STAT 266, STAT 276, KIN 109, PEDS 109, PSYCH 211, PTHER 352, SCI 151 or SOC 210.

LECTURE A2 (51234)

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



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 EA1 (47812)

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

Winter Term 2025 (1900)

STAT 151 - Introduction to Applied Statistics I

3 units (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. Notes: (1) Credit can be obtained in at most one of STAT 151, STAT 161, and STAT 235. (2) This course may not be taken for credit if credit has been obtained in STAT 222, STAT 266, STAT 276, KIN 109, PEDS 109, PSYCH 211, PTHER 352, SCI 151 or SOC 210.

LECTURE T2 (73502)

2025-01-06 - 2025-04-09
MWF 14:00 - 14:50



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 ER1 (73313)

2025-01-06 - 2025-04-09
TR 11:00 - 12:20

LECTURE EQ1 (73530)

2025-01-06 - 2025-04-09
TR 08:00 - 09:20