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DoaneX: BioStatistics

This college-level Biostatistics course will teach you the skills required for success in future analytical studies in biology.

This course is eligible for Audit and Verified Certificate only.

BioStatistics
8 weeks
5–10 hours per week
Self-paced
Progress at your own speed
Free
Optional upgrade available

There is one session available:

26,651 already enrolled! After a course session ends, it will be archivedOpens in a new tab.
Starts Nov 27

About this course

Skip About this course

In this undergraduate-level biostatistics course, the learners will be introduced to the use of statistics and study designs in biology. Upon successful completion of this course, learners will be able to design experimental, quasi-experimental and observational studies that will meet regulatory guidelines; collect, analyze, and interpret data using appropriate statistical tools. These are skills utilized in bio-statistical research in healthcare as well as other biology related fields. The importance of having these skills is recognized within public health sectors relating to analysis of drug effectiveness and risk factors for different illnesses, effectiveness of heath care interventions as well as helping explain biological phenomena.

In addition to fulfilling requirements in undergraduate college programs, this undergraduate level course also provides future healthcare professionals with foundational coursework required for successful entry into a health professions graduate program or medical school. This course may also spark further interest for the learner towards a more advanced degree in biostatistics. The field of biostatistics provides an increasing opportunity for employment. According to the United States Bureau of Labor Statistics, this field will experience a 14% employment growth between 2010 and 2020.

At a glance

  • Language: English
  • Video Transcript: English
  • Associated skills:Biostatistics, Public Health, Apache Spark, Biology, Auditing, Academic Integrity

What you'll learn

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  • Identify different types of data, and how it can be collected
  • Recognize and design simple experiments
  • Summarize data numerically and graphically using R
  • Understand the difference between point and interval estimation
  • Determine and perform correct statistical test
  • Conclude and interpret the results from those tests

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