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Biostatistics: Getting Started

This guide covers material for Biostatistics I (OCOR 5603 and BCOR 5570) and Biostatistics II (OCOR 5606 and BCOR 5575).

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Biostatistics

Biostatistics

Course Numbers:

Biostatistics I: OCOR 5603; BCOR 5570

Biostatistics II: OCOR 5606; BCOR 5575

Biostatistics I:

This graduate course will introduce the most commonly used statistical tests and procedures to analyze biological and ecological data. The main objective is to prepare the students to identify the most corrrect statistics to analyze biological data, perform the statistical analysis in R Studio and correctly interpret the results. Lectures will consist of short theoretical presentations followed by a lab where students will do guided exercises in R Studio. Students will be required to do readings prior to the class on the theoretical basis of the theme of the week, and perform unguided exercises (homework) to cement knowledge.

Biostatistics II:  

This is an intermediate/advanced course in the practical applications of descriptive and inferential statistics with emphasis on advanced methods of analyzing biological data. Topics will include: analysis of variance (ANOVA); data transformations; linear regression and correlation; power analysis; goodness-of-fit tests; and non-parametric methods. Additional topics may include multiple and curvilinear regression techniques. Handouts of the overheads will be generated each week to help minimize the amount of writing on the board and note taking.

Biostatistics

Course Numbers:

Biostatistics I: OCOR 5603; BCOR 5570

Biostatistics II: OCOR 5606; BCOR 5575

Biostatistics I Textbook:

Biostatistics I Suggested Books:

Biostatistics II Textbook:

Requirements for Both Courses:

There will also be supplemental readings provided, related to R and data analysis

Required Course Statistical Package:

Biostatistics

Course Numbers:

Biostatistics I: OCOR 5603; BCOR 5570

Biostatistics II: OCOR 5606; BCOR 5575

 

Biostatistics I:

  • Describe critical aspects of the data such as scales of measurement
  • Identify if the variables are discrete or continuous
  • Calculate summary statistics.
  • Create appropriate graphs, charts, maps, and tables to represent data.
  • Determine the appropriateness of various statistical tests and procedures for analyzing different types of biological data
  • Analyze biological data using the appropriate statistical test(s) in software R
  • Correctly interpret results of statistical analysis
  • Write a grammatically perfect, technically informed, well-structured document with regards to data analysis.

Biostatistics II:

  • Further enhance the understanding of the foundations of statistical thinking and analysis
  • Use more advanced statistical methods to analyze sample data and make inferences about the population of interest
  • Increase the understanding of using appropriate statistical software packages to conduct statistical analyses
  • Learn to interpret results of more advanced statistical analyses
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