Erin Curran portrait

Erin Curran

Associate Professor and Chair
Degree
Ph.D., Research Methodologies: Quantitative Methods and Measurement, University of North Dakota
B.S., Occupational Therapy, School of Medicine and Health Sciences, University of North Dakota
Office
OSS 403
Phone
(651) 962-5397
Toll Free
(800) 328-6819 x5397
Mail
University of St. Thomas
Mail Number OSS 402
2115 Summit Avenue
St. Paul, MN 55105

Professional Interests

Research:  Transformational Learning in Higher Education, Applied Statistics Education, Psychometric Analysis, Assessment and Evaluation in Education.
Teaching:  Applied Statistics, Psychometrics, Biometrics, Quantitative Research Methods, Assessment and Evaluation in Education. 

Summer 2018 Courses

Summer 2018 Courses
Course - Section Title Days Time Location
STAT 220 - 01 Statistics I See Details * *

Days of Week:

See Details

Time of Day:

*

Location:

*

Course Registration Number:

30031 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Erin M. Curran

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 NOTE: This is a hybrid section of STAT 220 where approximately 50% of course topics will be addressed through face-to-face instruction on scheduled class days. This means that roughly 50% of STAT 220 topics will be addressed through online and independent learning activities assigned by the instructor. These activities will be completed on students’ own time and in accordance with the class schedule. Homework will be assigned in addition to online and independent learning activities. All exams will be completed on campus during a scheduled face-to-face class period. While this class format will offer students a great deal of flexibility in learning assigned coursework, strong self-directed learning and time management skills will be essential for success.

Schedule Details

Location Time Day(s)
OSS 4291230-1430M - W - - - -
-- - - - - - -

Fall 2018 Courses

Fall 2018 Courses
Course - Section Title Days Time Location
STAT 220 - 04 Statistics I - T - R - - - 1330 - 1510 OWS 150

Days of Week:

- T - R - - -

Time of Day:

1330 - 1510

Location:

OWS 150

Course Registration Number:

40827 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Erin M. Curran

NOTE: Students registering for lecture STAT 220 04 must also register for lab 60, 61, or 62. Formerly IDTH 220. Statistics I is composed of an in-depth study of the processes through which statistics are applied in order to learn about environments and events. In this course, there is an intensive focus on the application, analysis, interpretation, and presentation of both descriptive and inferential statistics in myriad contexts. Topics covered include analytical and graphical tools for summarizing categorical and quantitative variables; correlation and simple linear regression; sampling strategies and research design; probability, probability models, and random variables; sampling distribution models; inference for one and two proportions; inference for one and two or more independent means; inference for paired means; inference for comparing counts; and inference for simple linear regression. Students must enroll in both a lecture section and software-specific laboratory section, in the same academic semester, to successfully complete STAT 220. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at MATH 108 or above; or MATH 100, 101, or 105. NOTE: Students who receive credit for STAT 220 may not receive credit for STAT 201.

Schedule Details

Location Time Day(s)
STAT 460 - 01 Statistical Research/Practicum - - - - - - - -

Days of Week:

- - - - - - -

Time of Day:

-

Location:

Course Registration Number:

41865 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Erin M. Curran

Students will work individually with the instructor to identify a statistical research topic of current interest or to identify a real practical problem, for which statistics can be used to produce a feasible solution. State and local governments, companies, businesses, TV channels, or even faculty doing research should be the natural source of real practical problems to be solved. For either the research or the practical problem, the final outcome should be a report with publication potential.

Schedule Details

Location Time Day(s)

J-Term 2019 Courses

J-Term 2019 Courses
Course - Section Title Days Time Location