Ph.D., M.S., University of Minnesota

B.A., Carleton College

Associate Professor and Chair

Degree

Ph.D., M.S., University of Minnesota

B.A., Carleton College

B.A., Carleton College

Office

OSS 403

Phone

(651)962-5471

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

My current academic interests are applied statistics, computer applications in experimental science, and STEM teacher preparation. In addition, I was the first Program Director for the new Statistics major at UST, fall 2009 to summer 2011.

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Course - Section | Title | Days | Time | Location | |
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CISC 321 - 01 | Systems Analysis and Design II | - T - R - | 1525 - 1700 | OSS 428 | |

Description of course Genetics B/ Lab: | CRN: 40843 4 Credit Hours (Formerly QMCS 421) Continuation of CISC 320. Concentration on user-centered design (UCD), physical design, low- and high- fidelity prototyping, and agile methods. Emphasis on managerial problems in systems development. Continued use of CASE and project-management tools. A "real world" design and prototyping project is an integral part of this course. Prerequisite: CISC 320 | ||||

STAT 220 - 04 | Statistics I | M - W - F | 0935 - 1040 | OEC 206 | |

Description of course Genetics B/ Lab: | CRN: 41142 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 - 05 | Statistics I | M - W - F | 1055 - 1200 | OEC 206 | |

Description of course Genetics B/ Lab: | CRN: 41143 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 |

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