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
German Pliego
Associate Professor
Degree
Office
OSS 410
Phone
(651)9625377
Toll Free
(800) 3286819 ext. 5377
Email
Mail
University of St. Thomas
Mail Number OSS 402
2115 Summit Avenue
St. Paul, MN 55105
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.
Spring 2016 Courses
Course  Section  Title  Days  Time  Location  

IDTH 360  01  Advanced Statistical Software   T  R     1330  1510  OSS 333  
Description of course Genetics B/ Lab: 
CRN: 22616
4 Credit Hours
Instructor: German J. Pliego Hernandez
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)
Schedule Details


STAT 220  10  Statistics I   T  R     0800  0940  OSS 329  
Description of course Genetics B/ Lab: 
CRN: 20847
4 Credit Hours
Instructor: German J. Pliego Hernandez
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, chisquare, 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
Schedule Details


STAT 220  12  Statistics I   T  R     0955  1135  OSS 329  
Description of course Genetics B/ Lab: 
CRN: 20849
4 Credit Hours
Instructor: German J. Pliego Hernandez
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, chisquare, 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
Schedule Details

Summer 2016 Courses
Course  Section  Title  Days  Time  Location 

Fall 2016 Courses
Course  Section  Title  Days  Time  Location 
