COURSES

Statistics.com's online professional development courses give you regular access to leading experts in statistics, in programs that fit your budget and schedule. You get access to a private discussion board with the instructor (often a leading expert and published author on the subject) for a period of 3-5 weeks. You should budget about 10-15 hours to work on each weekly lesson, arranged at your convenience (there are no set class hours). Most courses provide exercises with feedback, and many offer practical work with software. Several courses of study are available (e.g. biostatistics, environmental statistics, engineering statistics, etc.) in which you can earn a Program Certificate after completing the required courses.

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Introductory Begin Intro Begin Survey Intro Stats 1 Intro Stats 1 AP Intro Stats 2 Intro Stats 2 AP Intro Stats 3 Nonnormal Data Data Mining Cluster Analysis Data Mining 1 - Intro Data Mining 2 - Unsupervised Decision Trees Microarray Analysis Natural Language Processing Text Mining Life Science Adaptive Trials Biostatistics Clinical Trials Clinical-Bayes Epi 1 - Fundamentals Epi 2 - Bias Epi 3 - Analysis Meta Analysis Microarray Analysis Nonparametrics Survival Engineering DOE - Design Experiments DOE Advanced Engineering Risk Analysis SPC SPC Advanced Environment Environmental Environmental Bayesian Environmental Sampling Geostatistics Social Science Census Choice Modeling Facets GLM Longitudinal Data Nonparametrics Rasch Rasch Further SEM SEM Advanced Survey Analysis Survey Design Business Census Choice Modeling Data Mining 1 - Intro Data Mining 2 - Unsupervised Financial Risk Forecast 2 Forecasting National Income Natural Language Processing Risk Analysis Stat Methods Bayesian Statistics Bootstrap Categorical 1 Categorical 2 Cluster Analysis Count Data DOE - Design Experiments Engineering Forecast 2 GLM Logistic Regression Missing Data Mixed Models Multivariate Nonparametrics Randomization Regression Resampling SPC Advanced Sample Size Using R Microarray Analysis R Graphics R Intro (data) R Intro (stats) R Modeling