Introduction to Biostatistics
University of Otago
Dunedin, New Zealand
Area of Study
Exercise Biology, Health and Exercise Science, Health Science, Mathematics, Nutrition and Food Science, Statistics
Taught In English
STAT 110, (BSNS 102 or BSNS 112), QUAN 101
Course Level Recommendations
ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.
Recommended U.S. Semester Credits3 - 4
Recommended U.S. Quarter Units4 - 6
Hours & Credits
A course for students in health-related subjects, in particular nutrition, food science, epidemiology, exercise science, psychology, and the health sciences. Topics covered include the nature of random variation, the concepts of bias and confounding, study design, data description including risks and odds, binomial and normal distributions, estimation, hypothesis testing, regression, the control of confounders, critical appraisal, and the analysis of variance.
Biostatistics (statistics applied in the health sciences) is a vital tool in the mission to improve health and well-being for all people. STAT 115 provides an introduction to the core principles and methods of biostatistics. In this course you will gain an understanding of how statistics is used to answer research questions: how to look for patterns in data and how to test hypotheses about disease causation and prevention and improvement in well-being. The program 'R' will be used throughout the paper for data summary and statistical analysis. The understanding and skills gained in STAT 115 can be a starting point for a career in biostatistics or can be used to assist understanding of research in other disciplines including epidemiology, physiology, anatomy, human nutrition, sports science and psychology.
-Basic measures for describing data
-Introduction to statistical program 'R'
-Introduction to probability
-Binomial and normal distributions
-Estimation and confidence intervals
-Categorical data analysis
-Simple linear regression
-Regression procedures and the control of confounding
-The analysis of variation (ANOVA)
-Statistical issues in study design and critical appraisal of research
Students who successfully complete the paper will demonstrate awareness of and proficiency in the basics of objective statistical data analysis.
Courses and course hours of instruction are subject to change.
Eligibility for courses may be subject to a placement exam and/or pre-requisites.
Some courses may require additional fees.
Credits earned vary according to the policies of the students' home institutions. According to ISA policy and possible visa requirements, students must maintain full-time enrollment status, as determined by their home institutions, for the duration of the program.
Please reference fall and spring course lists as not all courses are taught during both semesters.
Availability of courses is based on enrollment numbers. All students should seek pre-approval for alternate courses in the event of last minute class cancellations
Please note that some courses with locals have recommended prerequisite courses. It is the student's responsibility to consult any recommended prerequisites prior to enrolling in their course.