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Statistical Inference

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Statistical Inference
Johns Hopkins University Online Course Highlights
  • weeks long
  • 16 hours to complete
  • Learn for FREE, Ugpradable
  • Self-Paced
  • Taught by: Brian Caffo, Jeff Leek, Roger D. Peng
  • View Course Syllabus

Online Course Details:

Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference. A practitioner can often be left in a debilitating maze of techniques, philosophies and nuance. This course presents the fundamentals of inference in a practical approach for getting things done. After taking this course, students will understand the broad directions of statistical inference and use this information for making informed choices in analyzing data.

WHAT YOU WILL LEARN

  • Describe variability, distributions, limits, and confidence intervals
  • Make informed data analysis decisions
  • Understand the process of drawing conclusions about populations or scientific truths from data
  • Use p-values, confidence intervals, and permutation tests

SKILLS YOU WILL GAIN

  • Statistics
  • Statistical Inference
  • Statistical Hypothesis Testing

Take This Online Course