German Pliego portrait

German Pliego

Associate Professor
Degree
ASQ Certified Quality Engineering, No. 36921, ASQC, June 1997.
Ph.D. 1991, Statistics, Purdue University
M.S. 1989, Mathematical Statistics, Purdue University
M.S. 1985, Decision Making, State of Mexico University
M.B.A. 1983, State of Mexico University
M.S. 1982, Statistics, Social Security Studies Center
M.S. 1982, Actuarial Sciences, Social Security Studies Center
B.S. 1977, Business Administration, State of Mexico University
Office
OSS 410
Phone
(651)962-5377
Mail
University of St. Thomas
Mail Number OSS 402
2115 Summit Avenue
St. Paul, MN 55105

Professional Interests

Areas of research:

•     Expert System: The Virtual Statistician
•     How to teach introductory statistics
•     Problem based learning and the teaching of statistics
•     Basic Statistical Problem Solver
•     Statistical applications in general
•     Statistics in pricing and valuing financial derivatives
•     Finding new ways of measuring volatility in energy markets
•     Sampling and surveys technically supported.
•     Quality Control: Shewhart control charts with flexible producer’s and consumer’s risks.

Summer 2014 Courses

Summer 2014 Courses
Course - Section Title Days Time Location
STAT 220 - 01 Statistics I M T W R - 1015 - 1215 OSS 313
CRN: 30051 4 Credit Hours Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chi-square, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201

Fall 2014 Courses

Fall 2014 Courses
Course - Section Title Days Time Location
IDTH 360 - 01 Advanced Statistical Software - - - - - -
CRN: 43431 Credit Hours This course introduces students to an advanced statistical software package to effectively apply statistical methods, in general. Students create data sets from raw data files, create variables within a data set, append and/or modify data sets, create subsets, then apply a whole host of statistical procedures, create graphs and produce reports. The course will be based on several leading advanced statistical software packages, which will be chosen from semester to semester to match the needs of the community. Prerequisites: MATH 113, STAT 220 Statistics I or STAT 314 Math Statistics (MATH 314)
IDTH 410 - 01 Operations Research I - - - - - -
CRN: 43432 Credit Hours (Formerly QMCS 410) Introduction to computer and analytic techniques to support the decision-making process. Topics include: Introduction to linear programming algorithms, sensitivity, duality, transportation, assignment, transshipment, integer linear programming, network models, project scheduling, inventory models, and waiting line models. Prerequisites: MATH 113 or MATH 114 or MATH 128; and either STAT 220 (IDTH 220) or STAT 314 (MATH 314)
STAT 220 - 09 Statistics I - T - R - 0800 - 0940 OSS 313
CRN: 41147 Credit Hours Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chi-square, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
STAT 220 - 12 Statistics I - T - R - 0955 - 1135 OSS 329
CRN: 41150 4 Credit Hours Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chi-square, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
STAT 220 - 14 Statistics I - T - R - 1330 - 1510 OSS 313
CRN: 41440 4 Credit Hours Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chi-square, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201

J-Term 2015 Courses

J-Term 2015 Courses
Course - Section Title Days Time Location