printer friendly pagePHIL 162: Philosophy of Mathematics (MATH 162, PHIL 262)
(Graduate students register for
PHIL 262.) 20th-century approaches to the foundations and philosophy of mathematics. The background in mathematics, set theory, and logic. Schools and programs of logicism, predicativism, platonism, formalism, and constructivism. Readings from leading thinkers. Prerequisite: PHIL151 or consent of instructor.
| UG Reqs: GER:DB-Math
PSYCH 10: Introduction to Statistical Methods: Precalculus (STATS 60, STATS 160)
Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of hypotheses, t-tests, correlation, and regression. Possible topics: analysis of variance and chi-square tests, computer statistical packages.
Terms: Aut, Win, Spr, Sum
| Units: 5
| UG Reqs: GER:DB-Math, WAY-AQR, WAY-FR
Instructors:
Bacallado, S. (PI)
;
Baiocchi, M. (PI)
;
Rabbee, N. (PI)
...
more instructors for PSYCH 10 »
Instructors:
Bacallado, S. (PI)
;
Baiocchi, M. (PI)
;
Rabbee, N. (PI)
;
Thomas, E. (PI)
;
Walther, G. (PI)
;
Yanes, R. (PI)
;
Diaz, M. (TA)
;
Dobriban, E. (TA)
;
He, J. (TA)
;
Hoffmann Bion, R. (TA)
;
Humphries, A. (TA)
;
LaRocque, K. (TA)
;
Lewis, M. (TA)
;
Manke, K. (TA)
;
Rodriguez, C. (TA)
;
Sorenson, J. (TA)
;
Wang, C. (TA)
;
Wisdom, A. (TA)
;
Yanes, R. (TA)
STATS 60: Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 160)
Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of hypotheses, t-tests, correlation, and regression. Possible topics: analysis of variance and chi-square tests, computer statistical packages.
Terms: Aut, Win, Spr, Sum
| Units: 5
| UG Reqs: GER:DB-Math, WAY-AQR, WAY-FR
STATS 90: Mathematics and Statistics in the Real World (MATH 16)
This is an introductory quantitative literacy course, that offers an introduction to the mathematics (outside of calculus) used in real-world problems. Topics include: (a) Exponential functions, compound interest, population growth. (b) Geometric series, applications to mortgage payments, amortization of loans, present value of money, drug doses and blood levels. (c) First-order approximation, estimating areas and volumes. (d) Basic probability: Bayes's rule, false positives in disease detection and drug testing. (e) Basic descriptive statistics: mean, median, standard deviation f) Least squares and linear regression.
Terms: Win
| Units: 3
| UG Reqs: GER:DB-Math
Instructors:
Khare, A. (PI)
;
Rajaratnam, B. (PI)
STATS 110: Statistical Methods in Engineering and the Physical Sciences
Introduction to statistics for engineers and physical scientists. Topics: descriptive statistics, probability, interval estimation, tests of hypotheses, nonparametric methods, linear regression, analysis of variance, elementary experimental design. Prerequisite: one year of calculus.
Terms: Aut, Sum
| Units: 4-5
| UG Reqs: GER:DB-Math, WAY-AQR, WAY-FR
STATS 116: Theory of Probability
Probability spaces as models for phenomena with statistical regularity. Discrete spaces (binomial, hypergeometric, Poisson). Continuous spaces (normal, exponential) and densities. Random variables, expectation, independence, conditional probability. Introduction to the laws of large numbers and central limit theorem. Prerequisites:
MATH 52 and familiarity with infinite series, or equivalent.
Terms: Aut, Spr, Sum
| Units: 3-5
| UG Reqs: GER:DB-Math, WAY-AQR, WAY-FR
Instructors:
Bacallado, S. (PI)
;
Dobriban, E. (PI)
;
Gao, K. (PI)
...
more instructors for STATS 116 »
Instructors:
Bacallado, S. (PI)
;
Dobriban, E. (PI)
;
Gao, K. (PI)
;
Guillot, D. (PI)
;
Khare, A. (PI)
;
Reid, S. (PI)
;
Basak, A. (TA)
;
Basu, K. (TA)
;
Mukherjee, S. (TA)
;
Wang, C. (TA)
STATS 141: Biostatistics (BIO 141)
Introductory statistical methods for biological data: describing data (numerical and graphical summaries); introduction to probability; and statistical inference (hypothesis tests and confidence intervals). Intermediate statistical methods: comparing groups (analysis of variance); analyzing associations (linear and logistic regression); and methods for categorical data (contingency tables and odds ratio). Course content integrated with statistical computing in R.
Terms: Aut
| Units: 3-5
| UG Reqs: GER:DB-Math, WAY-AQR
Instructors:
Li, L. (PI)
;
Su, W. (TA)
STATS 167: Probability: Ten Great Ideas About Chance (PHIL 166, PHIL 266, STATS 267)
Foundational approaches to thinking about chance in matters such as gambling, the law, and everyday affairs. Topics include: chance and decisions; the mathematics of chance; frequencies, symmetry, and chance; Bayes great idea; chance and psychology; misuses of chance; and harnessing chance. Emphasis is on the philosophical underpinnings and problems. Prerequisite: exposure to probability or a first course in statistics at the level of
STATS 60 or 116.
Terms: Spr
| Units: 4
| UG Reqs: WAY-AQR, WAY-FR, GER:DB-Math
STATS 191: Introduction to Applied Statistics
Statistical tools for modern data analysis. Topics include regression and prediction, elements of the analysis of variance, bootstrap, and cross-validation. Emphasis is on conceptual rather than theoretical understanding. Applications to social/biological sciences. Student assignments/projects require use of the software package R. Recommended: 60, 110, or 141.
Terms: Aut
| Units: 3-4
| UG Reqs: GER:DB-Math, WAY-AQR
Instructors:
Taylor, J. (PI)
UGXFER GER2C1: GER 2C SUBSTITUTION (1ST)
| UG Reqs: GER:DB-Math
| Repeatable
for credit
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