MATHEMATICAL SCIENCES

Faculty
T. V. Craine (Chair); F. Bensics, R. Bilisoly, N. Castaneda, Y. Chen, R. Crouse, D. Dzuida, V. Gochev, I. Gotchev, S. L. Gould, P. Halloran, C. Jin (Asst. Chair), S. Jones, R. S. Kalder, D. T. Larose, F. Latour, S. Lesik, E. Makover, M. Matsushita, J. McGowan (Asst. Chair), A. Miller, D. S. Miller, M. Mitchell, L. Recoder-Núñez, T. Roman, K. Saha, C. D. Smith, R. Vogeler, C. Waiveris, P. Weisgram
(Dept. phone 832-2835)

Department Overview
The Department of Mathematical Sciences offers programs leading to the Master of Science and Master of Arts degrees. Master of Arts candidates may specialize in mathematics, computer science, statistics, or actuarial mathematics. Master of Science candidates may pursue a program for certified elementary or secondary school teachers or enroll in the data mining program. Students may also enroll in a program leading to certification to teach mathematics at the secondary level.

Programs
MASTER OF SCIENCE IN MATHEMATICS FOR CERTIFIED ELEMENTARY TEACHERS
(Plans A and C are offered as options. No more than nine credits at the 400 level may be counted toward the degree.)

Professional Education (3 credits):
One of the following:
EDF 500 Contemporary Educational Issues
EDF 516 School and Society
EDF 524 Foundations of Contemporary Theories of Curriculum
EDF 525 History of American Education
EDF 538 The Politics of Education
EDF 583 Sociological Foundations of Education

Elementary/Middle School Mathematics Education Core (12 credits):
Elementary school track:
MATH 506 Teaching Number Concepts in the Elementary Grades
MATH 507 Teaching Geometry and Measurement in the Elementary Grades
MATH 508 Teaching Probability and Statistics in the Elementary Grades
MATH 509 Teaching Algebraic Thinking in the Elementary Grades
or
Middle school track:
MATH 536 Teaching Number Concepts in the Middle Grades
MATH 537 Teaching Geometry and Measurement in the Middle Grades
MATH 538 Teaching Probability and Statistics in the Middle Grades
MATH 539 Teaching Algebraic Thinking in the Middle Grades

Mathematics Electives (6 credits):
Choose two courses from
MATH 449 Mathematics Laboratory for Elementary School
MATH 504 Topics in Mathematics
MATH 534 Techniques in Diagnosis and Remediation for the Teaching of Mathematics K–12
MATH 580 Directed Study in Mathematics
STAT 453 Applied Statistical Inference

General Electives (6 credits):
Courses chosen from the electives listed above, graduate education courses and MATH 531, as approved by faculty advisor.

Research (3 credits):
MATH 598 Research in Mathematics Education

Capstone:
Plan A: 33 credits consisting of 30 credits from the above listings plus MATH 599 (3 credit Thesis).

Plan C: 33 credits consisting of 30 credits from the listings above plus MATH 590 Special Project in Mathematics (3 credits).

Note: Once a graduate student has elected one of the two plans, A or C, any change to the other plan must be made prior to the completion of 21 graduate credits and requires the approval of the student’s advisor and the Dean, School of Graduate Studies.

MASTER OF SCIENCE IN MATHEMATICS FOR CERTIFIED SECONDARY TEACHERS
(Plans A and C offered as options. No more than nine credits may be earned in 400-level courses.)

General Education Electives (3 credits):
As approved by faculty advisor

Educational Foundations (3 credits):
Chosen from EDF 500, 516, 524, 525, 538 or 583

Secondary Mathematics Education (9 credits):
MATH 547 plus 6 credits chosen from MATH 504, 534, 540, 543, 544 and 580

Mathematics and Statistics Content
Courses (12 credits):
No more than six credits in courses with the STAT designation. One course must be STAT 453 unless this course was taken as an undergraduate. Courses to be chosen from MATH 421, 440, 468, 469, 470, 477, 491, 515, 516, 519, 520, 523, 525, 526, STAT 453, 455, 567

Research in Mathematics Education (3 credits): MATH 598

Capstone:
Plan A: 33 credits consisting of 30 credits from the above plus MATH 599 (3 credit thesis)

Plan C: 33 credits consisting of 30 credits from the above plus MATH 590 (3 credit-Special Project)

Note: Once a graduate student has elected one of the two plans, A or C, any change to the other plan must be made prior to the completion of 21 graduate credits and requires the approval of the student’s advisor and the Dean, School of Graduate Studies.

MASTER OF ARTS IN MATHEMATICS
This program is designed for those students who wish to expand their knowledge of mathematics beyond the level of undergraduate study, either as preparation for advanced graduate study or to increase their knowledge of mathematics for teaching, or to combine a knowledge of higher mathematics with related mathematical sciences and computer science for a career in industry.
Applicants to the Master of Arts program are expected to have completed the equivalent of MATH 152, 221, 222, 228 and 366 in addition to any necessary prerequisites for courses required in the planned program of graduate study.

M.A. Program in Mathematics—General
30 credits
Requirements (18 credits):
MATH 515 Abstract Algebra I
MATH 516 Abstract Algebra II
MATH 519 Principles of Real Analysis I
MATH 520 Principles of Real Analysis II
MATH 523 General Topology
MATH 526 Complex Variables

Electives as approved by faculty advisor (12 credits).
These may include 3 credits for the thesis for a student electing Plan A. No more than 9 credits may be earned from 400-level courses.

Capstone Experience:
Plan A: Thesis (MATH 599, 3 credits). Students electing this option must also pass one qualifying examination* in an area not related to the thesis topic.
Plan B: Comprehensive Exam. Students selecting this option must pass two of three qualifying examinations* (in the areas of algebra, analysis, or topology) and also give oral presentations on a topic approved by their advisor.

* Students must apply for qualifying examinations after completing appropriate coursework with the approval of their advisors. Applications are available in the School of Graduate Studies or on the web at www.ccsu.edu/grad under Graduate Forms (Degree Candidacy/Non Capstone Qualifying Form).

M.A. Program in Mathematics with Specialization in Computer Science
30 credits
The student will choose a specialization in computer programming techniques and numerical methods or computer systems and software engineering. The student and faculty advisor will work out an appropriate plan of study within the framework of the following requirements.

Requirements:
Basic Mathematics Courses (12 credits) — Three (3) of MATH 515, 516, 519 and 520; and one (1) of MATH 523, 526 and STAT 551.

Electives appropriate to the area of specialization as approved by the faculty advisor (18 credits); no more than nine of these credits may be earned in 400-level courses.

Comprehensive Examination

M.A. Program in Mathematics with Specialization in Actuarial Science
(Plans A, B and C are offered as options.)
The student and faculty advisor will work out an appropriate plan of study within the framework of the following requirements.

Requirements:
Actuarial Core (8 credits): Actl 565 and 566

Additional courses as approved by the advisor, including:
a. 9 credits chosen from ACTL 480, 481, 482, 580,
b. 9 credits designated STAT or MATH at the 400 or 500 level, and
c. 1–4 additional credits in actuarial science, mathematics, or statistics.
No more than nine credits in the program may be earned in 400-level courses.

Capstone:
Plan A: Thesis (Math 599, 6 credits) with 27 credits of course work
Plan B: Comprehensive Exam with 30 credits of course work
Plan C: Special Project in Mathematics (MATH 590, 3 credits) with 30 credits of course work

M.A. Program in Mathematics with Specialization in Statistics
(Plans A, B and C are offered as options.)

The student and faculty advisor will work out an appropriate plan of study within the framework of the following requirements.

Requirements:
Statistics Core (6 credits): STAT 567 and 575

Three courses chosen from ACTL 565, 566; MATH 470, 477, 519, 520; STAT 551 (9–11 credits)

Electives appropriate to the area of specialization (10–15 credits): No more than nine credits in the program may be earned in 400-level courses.

Capstone:
Plan A: Thesis (Math 599) (6 credits) with 27 credits of course work
Plan B: Comprehensive Exam with 30 credits of course work
Plan C: Special Project in Mathematics (MATH 590) (3 credits) with 30 credits of course work.

Note: Once a graduate student has elected one of the three plans A, B or C, any change to one of the other plans must be made prior to the completion of 21 graduate credits and requires the approval of the student’s advisor and the Dean, School of Graduate Studies.

MASTER of SCIENCE IN DATA MINING
Admission Requirements
The minimum required undergraduate GPA for prospective candidates for the Master of Science in data mining is 3.00. Conditional admission may be granted to candidates with undergraduate GPAs as low as 2.40, conditioned on a student receiving no grades lower than an A- in the first three core courses in the program.
The following materials are required, in addition to the materials required by the School of Graduate Studies.
1. A formal application essay of 500–1000 words that focuses on (a) academic and work history, (b) reasons for pursuing the Master of Science in data mining, and (c) future professional aspirations. The essay will also be used to demonstrate a command of the English language.
2. A detailed, itemized letter explaining whether and how the candidate has fulfilled each of the program prerequisites that applicants to the Master of Science in data mining program are expected to have completed, or be in the process of completing:
• MATH 221 Calculus II;
• STAT 315 Mathematical Statistics I; and
• a second-semester course in undergraduate statistics. Students may be admitted on condition that they complete these prerequisite courses with a grade of B or better. These prerequisite courses are regularly offered in the classroom, and some may be offered online, for students who are missing one or more of these courses.
In their letters, candidates are asked to show which courses on which transcripts are being used to fulfill each of these prerequisites. In particular, the candidate is asked to consider that mathematical statistics is calculus-based and represents a different approach beyond the usual undergraduate statistics course. Therefore, a course description or syllabus for the mathematical statistics course should be attached to the letter. If a candidate has not had courses that would fulfill certain program prerequisites, the candidate should so indicate. The candidate is reminded that conditional admission may be granted for students needing to complete any or all of the program prerequisites.
3. Two letters of recommendation, one each from the academic and work environment (or two from academia if the candidate has not been employed).

The application and all transcripts should be sent to the Graduate Admissions Office. The deadline for submitting applications for the fall semester is May 1. The other materials, including the formal application essay, the prerequisites letter, and the two letters of recommendation, should be sent to:
Dr. Daniel T. Larose
Re: MS in Data Mining Admissions Materials
Department of Mathematical Sciences
Marcus White 118
Central Connecticut State University
New Britain, CT, 06050

Note: Only hard copy materials are acceptable. No attachments to e-mails or other electronically transmitted material will be considered in admissions decisions.

M.S. in Data Mining
36 credits
Core Courses (27 credits)
The following courses are required of all students. (All courses three credits unless otherwise indicated.)
STAT 416 Mathematical Statistics II
STAT 521 Introduction to Data Mining (4 credits)
STAT 522 Data Mining Methods (4 credits)
STAT 523 Applied Data Mining (4 credits)
STAT 525 Web Mining
STAT 526 Data Mining for Genomics and Proteomics
STAT 527 Text Mining
STAT 570 Applied Multivariate Analysis

Thesis Course (3 credits)
STAT 599 Thesis
All students must elect capstone Plan A, thesis. Students must make a presentation of their thesis on the CCSU campus. Students who cannot come to campus must make a web presentation of their thesis.

Elective Courses (6 credits)
Choose any two courses from the following list:
CS 570 Topics in Artificial Intelligence
CS 580 Topics in Database Systems and Applications
STAT 455 Experimental Design
STAT 529 Current Issues in Data Mining
STAT 551 Applied Stochastic Processes
STAT 567 Linear Models
STAT 575 Mathematical Statistics III
Other appropriate graduate course, with permission of advisor

Note: New students may take the first course in the program while working on the prerequisites for the more advanced courses.

Note: No more than nine credits at the 400 level, as approved by the graduate advisor, may be counted toward the graduate planned program of study.

NEW!   Graduate Certificate in Data Mining (18 Credits)

Required Courses (12 Credits)

• Stat 521 Introduction to Data Mining (4 credits)
• Stat 522 Data Mining Methods and Models (4 credits)
• Stat 523 Applied Data Mining (4 credits)

Elective Courses (6 Credits) 
Choose two of:

• Stat 525 Web Mining
• Stat 526 Data Mining for Genomics and Proteomics
• Stat 527 Text Mining
• Stat 529 Current Issues in Data Mining
• Some other graduate-level data mining or statistics course, with approval of program coordinator.

Current Students
All students who have been admitted (not conditionally admitted) to the Graduate Certificate in Data Mining should download the 2007 Planned Program of Study, complete as much of it as you can, and email to Dr. Larose at larosed@ccsu.edu.

Students who have been conditionally admitted, and have completed their conditions, should notify Dr. Larose at larosed@ccsu.edu, so that you may be fully and officially admitted.

Cost
All data mining majors are classified for business purposes as part-time students, with a premium rate, see here.

Program Prerequisites
Applicants to the Graduate Certificate program in Data Mining program are expected to have completed, or be in the process of completing, a second semester course in undergraduate or graduate statistics.  Students may be admitted on condition that they complete these prerequisite courses with a grade of B or better.   

Admission Criteria  
Students must hold a bachelor’s degree from a regionally accredited institution of higher education. The undergraduate record must demonstrate clear evidence of ability to undertake and pursue studies in a graduate field successfully.  A minimum undergraduate GPA of 3.00 on a 4.00 point scale (where A is 4.0), or its equivalent, and good standing (3.0 GPA) in all post-baccalaureate course work is required.  Conditional admission may be granted to candidates with undergraduate GPA’s as low as 2.4, conditioned on the students getting no grades lower than a B in their first three core courses in the program. 

The following materials are required, in addition to the materials required by the School of Graduate Studies.  (1) A formal application essay of 500 – 1000 words that focuses on (a) academic and work history, (b) reasons for pursuing the Graduate Certificate in Data Mining, and (c) future professional aspirations.  The essay will also be used to demonstrate a command of the English language.  (2) A detailed, itemized letter explaining whether and how the candidate has fulfilled the program prerequisites that applicants to the Graduate Certificate in Data Mining program are expected to have completed, or be in the process of completing:  a second semester course in undergraduate or graduate statistics.  In their letter, candidates are asked to show which courses on which transcripts are being used to fulfill each of these prerequisites.  If a candidate has not had courses that would fulfill certain program prerequisites, the candidate should so indicate.  The candidate is reminded that conditional admission may be granted for students needing to complete any or all of the program prerequisites.  (3) Two letters of recommendation.

The application and all transcripts should be sent to the Graduate Admissions Office.  The other materials, including the formal application essay, the prerequisites letter, and the two letters of recommendation, should be sent to: 

Dr. Daniel T. Larose
Re: Graduate Certificate in Data Mining Admissions Materials
Department of Mathematical Sciences
Marcus White 118
Central Connecticut State University
New Britain, CT, 06050  

Note that only hard copy materials are acceptable.  No attachments to emails or other electronically transmitted material will be considered in admissions decisions.  

Can I start out with the Certificate program, and then transfer those courses to the Master of Science program?
Yes.  However, the student will need to apply for the MS program separately.  The mathematical and statistical requirements for the MS program are more stringent than for the Certificate program.

POST BACCALAUREATE TEACHER CERTIFICATION PROGRAM IN SECONDARY MATHEMATICS
35 credits
Admission criteria:
a) The candidate must qualify for admission to the University’s graduate programs, including a 2.70 minimum GPA.
b) The candidate must have completed at least 30 credits in mathematics content courses.
c) The candidate must meet all requirements for admission to the Professional Program for Teacher Education, including passing scores on Praxis I or waiver and an interview with and a positive recommendation by the Acceptance Committee of the Department of Mathematical Sciences.

Required courses: EDF 415,* RDG 504, EDTE 315,* EDSC 425,* EDSC 435,* SPED 501, MATH 413,* MATH 426,* MATH 543, MATH 544.

* No credit toward a graduate degree

Students may also take up to nine credits in graduate-level mathematics courses to complete as much as 21 credits toward a M.S. degree in Secondary Mathematics during this 14-month program. A maximum of nine credits at the 400 level may be counted toward the M.S. degree, upon approval by the faculty advisor.