Welcome to the CoursePlus Web site for STATISTICS FOR LABORATORY SCIENTISTS I (140.615.01), a course offered by the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health.
Introduces the basic concepts and methods of statistics with applications in the experimental biological sciences. Demonstrates methods of exploring, organizing, and presenting data, and introduces the fundamentals of probability. Presents the foundations of statistical inference, including the concepts of parameters, estimates, and the use of confidence intervals and hypothesis tests. Topics include experimental design, linear regression, the analysis of two-way tables, and sample size and power calculations. Introduces and employs the freely available statistical software, R, to explore and analyze data.
Upon successfully completing this course, students will be able to:
- Create appropriate statistical graphics
- Identify flaws in experimental designs and observational studies, and form appropriate simple experimental designs
- Explain confounding and identify potential confounding factors in an observational study
- Solve simple probability problems
- Calculate and interpret confidence intervals for the difference between two populations' means and for a population proportion
- conduct simple tests of statistical hypotheses and calculate and interpret P-values from such tests
- Calculate power and minimal sample size for simple experiments
- Use the statistical software, R, to display and analyze data
Mon Wed Fri 10:30 AM to 11:20 AM
Laboratory science students in BMB, EHS, MMI, and IH (nutrition)
Grading Policy: Homework assignments, one or two in-class exams
Grading Restrictions: Letter grade