NC State Department of Statistics



Graduate Certificate Programs in Statistics

1. Motivation

The Department of Statistics at North Carolina State University wishes to establish Graduate Certificate Programs (GCP's) in the following three areas: Applied Statistics, Statistical Computing, and Statistical Education. We are experiencing a great demand for students trained in statistics, and our graduate programs at the master’s and doctoral levels have both a high number of applications and high demand for our graduates. However, these efforts do not address the demand for skills below a Master's degree and the Graduate Certificate provides the appropriate credential for many of these jobs. In particular, many individuals with general scientific training are doing statistics and learning on-the-job. For these individuals, a Certificate in Applied Statistics would give them the credentials to allow them to advance or change jobs. Others with minimal statistics training could use the Certificate in Statistical Computing to qualify for Statistical Programmer positions. Instructors with a strong mathematics background but little statistics could qualify for teaching Statistics with a Certificate in Statistical Education.

2. Coordinator

The Coordinator for the Graduate Certificate Programs in the Department of Statistics will be Dr. Roger Woodard, the Director of Online Programs.

3. Application Process/Admissions Requirements

A student admitted to the GCP must satisfy the basic NC State admissions requirements for admission to graduate study (BS/BA, GPA > 3.0 -- with the usual provisional admission). We recommend that students apply after completing two of the courses required for the GCP to which they apply with grades at least B. Applications will also be considered if a student has successfully completed the second course of a methods sequence (ST508/ ST512/ ST514). The Coordinator will manage the admissions process.

4. Admission to other graduate programs

"Academic success might have a strong bearing on admission to a degree program BUT completion of a certificate program in no way guarantees entry into a graduate degree program which is done through a separate application process."

5. Course Requirements for Proposed GCP's

All three proposed programs require four courses (12 credits) of which two are graduate statistical methods courses. The course requirements are:

a) Certificate in Applied Statistics: ST511, ST512, ST555, and one elective (see below)

b) Certificate in Statistical Computing: ST513, ST514, ST555, ST556

c) Certificate in Statistics Education: ST507, ST508, ST519, ST557

The full titles for these courses are:

ST507 - Statistics for the Behavioral Sciences I

ST508 - Statistics for the Behavioral Sciences II

ST511 - Experimental Statistics for Biological Sciences I

ST512 - Experimental Statistics for Biological Sciences II

ST513 - Statistics for Management I

ST514 - Statistics for Management and Social Sciences II

ST519 - Teaching and Learning of Statistical Thinking

ST555 - Statistical Computing I

ST556 - Statistical Computing II

ST557 - Teaching Statistics with Technology

Notes:

i) Due to the nature of these courses and the backgrounds of potential students, we will allow students to substitute among the statistical methods sequences: ST507/508, ST511/512, ST513/514. For example, a student taking ST511 and ST514 would satisfy the graduate methods requirement.

ii) If students have already completed a course similar to the initial course (ST507/511/513) of the statistical methods sequences, and complete the second course in the sequence successfully (at least B), then they can substitute an elective for the initial course.

iii) Electives may be chosen from the following:

ST505 Applied Nonparametric Statistics

ST519 Teaching and Learning of Statistics

ST520 Clinical Trials and Epidemiology

ST524 Statistics in Plant Science

ST555 Statistical Computing I

ST556 Statistical Computing II

ST557 Teaching Statistics with Technology

ST708 Applied Least Squares

ST711 Design of Experiments

ST715 Theory of Sampling

ST730 Applied Time Series

ST731 Applied Multivariate Analysis

ST732 Applied Longitudinal Analysis

ST733 Applied Spatial Statistics

ST744 Categorical Data Analysis

ST745 Analysis of Survival Data

6. Contact:

Dr. John Monahan (monahan@ncsu.edu) 515-1917

Dr. Roger Woodard (woodard@stat.ncsu.edu) 515-1938

7. Student Learning Outcomes and Assessment

The final exams or final projects from the student’s courses will be kept on file as a representative portfolio of the student’s work. Each semester, each portfolio will be scored by at least two faculty members of the Statistics Online Committee for periodic assessment. These scores can then be used to track both student progress and instructional performance.

A student completing the Certificate in Applied Statistics is expected to be able to:

1) Correctly analyze and interpret the results from standard designed experiments and observational studies.

2) Demonstrate the computing skills to manage data and implement standard statistical methods.

3) Correctly apply the appropriate statistical techniques in at least one specialized area, such as time series, longitudinal, or spatial data.

|Outcome |Evidence |Source |When? |

|Correctly analyze and interpret the|Final Exams from ST507&508 or |Student |At end of semester |

|results from standard designed |ST511&512 or ST513&514 | | |

|experiments and observational | | | |

|studies. | | | |

|Demonstrate the computing skills to|Final Exam and Homeworks from ST555|Student |At end of semester |

|manage data and implement standard | | | |

|statistical methods. | | | |

|Correctly apply the appropriate |Final Exam/Project from elective |Student |At end of semester |

|statistical techniques in at least |course(s) | | |

|one specialized area, such as time | | | |

|series, longitudinal, or spatial | | | |

|data. | | | |

A Student completing the Certificate in Statistical Computing is expected to be able to:

1) Correctly analyze and interpret the results from standard designed experiments and observational studies.

2) Demonstrate the computing skills to gather, clean, and manage large, complex data.

3) Demonstrate the computing skills to apply statistical techniques to large, complex data sets in an automated fashion and assemble the results for interpretation.

|Outcome |Evidence |Source |When? |

|Correctly analyze and interpret the|Final Exams from ST507&508 or |Student |At end of semester |

|results from standard designed |ST511&512 or ST513&514 | | |

|experiments and observational | | | |

|studies. | | | |

|Demonstrate the computing skills to|Final Exam and Final Homework from |Student |At end of semester |

|manage data and implement standard |ST555, Homeworks from ST556 | | |

|statistical methods. | | | |

|Demonstrate the computing skills to|Final Homework from ST556 |Student |At end of semester |

|apply statistical techniques to | | | |

|large, complex data sets in an | | | |

|automated fashion and assemble the | | | |

|results for interpretation. | | | |

A Student completing the Certificate in Statistics Education is expected to be able to:

1) Correctly analyze and interpret the results from standard designed experiments and observational studies.

2) Construct modern lesson plans for teaching statistics courses

3) Choose and implement the use of technology in statistics courses

|Outcome |Evidence |Source |When? |

|Correctly analyze and interpret the|Final Exams from ST507&508 or |Student |At end of semester |

|results from standard designed |ST511&512 or ST513&514 | | |

|experiments and observational | | | |

|studies. | | | |

|Construct modern lesson plans for |Assignments and Quizzes from ST557 |Student |At end of semester |

|teaching statistics courses | | | |

|Choose and implement the use of |Assignments and Quizzes from ST557 |Student |At end of semester |

|technology in statistics courses. | | | |

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