| "Penn State Online has given me confidence in myself and I am able to do so much more in my life. The confidence comes from the self-discipline I didn't know I had until I started distance education." — Deborah Guy, undergraduate student
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Course List
Graduate Certificate in Applied Statistics (12 credits)
| Required Courses (6 credits) |
| STAT 500 |
Applied Statistics
Descriptive statistics, hypothesis testing, power, estimation, confidence intervals, regression, one- and two-way ANOVA, chi-square tests, diagnostics.
Prerequisite: 3 credits in statistics
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3 credits |
| STAT 501 |
Regression Methods
Analysis of research data through simple and multiple regression and correlation; polynomial models; indicator variables; step-wise, piece-wise, and logistic regression.
Prerequisites: 6 credits of statistics or STAT 500; matrix algebra
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3 credits |
| Elective Courses (6 credits)—choose the courses that best meet your goals from the following list |
| STAT 414 |
Introduction to Probability Theory
Probability spaces, discrete and continuous random variables, transformations, expectations, generating functions, conditional distributions, law of large numbers, central limit theorems. Students may take only one course from Stat (Math) 414 and Stat (Math) 418 for credit.
Prerequisite: MATH 230 or MATH 231
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3 credits |
| STAT 415 |
Introduction to Mathematical Statistics
A theoretical treatment of statistical inference, including sufficiency, estimation, testing, regression, analysis of variance, and chi-square tests.
Prerequisite: Stat (Math) 414
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3 credits |
| STAT 480 |
Introduction to Statistical Program Packages
Selection and evaluation of statistical computer packages.
Prerequisite: 3 credits in statistics |
1 credit |
| STAT 481 |
Intermediate SAS for Data Management
Intermediate SAS for data management.
Prerequisite: STAT 480 |
1 credit |
| STAT 502 |
Analysis of Variance and Design of Experiments
Analysis of variance and design concepts; factorial, nested, and unbalanced data; ANCOVA; blocked, Latin square, split-plot, repeated measures designs.
Prerequisite: STAT 462 or STAT 501 |
3 credits |
| STAT 503 |
Design of Experiments
Design principles; optimality; confounding in split-plot, repeated measures, fractional factorial, response surface, and balanced/partially balanced incomplete block designs.
Prerequisites: STAT 462 or STAT 501; STAT 502 |
3 credits |
| STAT 504 |
Analysis of Discrete Data
Models for frequency arrays; goodness-of-fit tests; two-, three-, and higher-way tables; latent and logistics models.
Prerequisites: STAT 500 and 501; matrix algebra |
3 credits |
| STAT 505 |
Applied Multivariate Statistical Analysis
Analysis of multivariate data; T-squared tests; partial correlation; discrimination; MANOVA; cluster analysis; regression; growth curves; factor analysis; principal components; canonical correlations.
Prerequisites: STAT 500 and 501; matrix algebra
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3 credits |
| STAT 506 |
Sampling Theory and Methods
Theory and application of sampling from finite populations.
Prerequisites: calculus; 3 credits in statistics
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3 credits |
| STAT 509 |
Design and Analysis of Clinical Trials
An introduction to the design and statistical analysis of randomized and observational studies in biomedical research.
Prerequisite: STAT 500 |
3 credits |
| STAT 510 |
Applied Time Series Analysis
Identification of models for empirical data collected over time. Use of models in forecasting.
Prerequisite: Stat 462, 501, or 511
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3 credits |
| STAT 557 |
Data Mining I
This course introduces data mining and statistical/machine learning, and their applications in information retrieval, database management, and image analysis.
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3 credits |
| GEOG 483 |
Problem-Solving with GIS
How geographic information systems facilitate data analysis and communication to address common geographic problems.
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3 credits |
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