# BIOL 4001: Biostatistics

This course explores the nature of data and the challenges involved in collecting and handling it, this includes planning the collection of data necessary to examine a particular problem, manipulation of data, summarizing and describing a data set. It also covers the statistical approach for testing hypotheses, and performing data analysis using current statistical tools as a tool for description and hypotheses testing. Students will also interpret and evaluate statistical analyses used by others, design experiments, and analyze and interpret the results of experiments or observational studies.

## Learning outcomes

• Identify statistical analyses necessary for successful research in biology
• Interpret descriptive statistics in the context of biological data.
• Use methods of inferential statistics to draw conclusions about biological phenomena.
• Describe the purpose of statistical analysis and the scientific method to study biology.
• Carry out data collection, construct hypotheses, analyze data, and apply statistical methods.
• Explain principles of good study design in the collection of data.
• Construct testable hypotheses to answer questions of interest.
• Analyze data to provide numerical and graphical data summaries.
• Apply statistical methods to make inferences about questions of interest.
• Use the R software environment for statistical analysis of data.
• Critically evaluate scientific studies based on their study design and statistical analyses.
• Communicate the purpose and methods of inferential statistics to audiences familiar with basic science.

## Course topics

• Course Introduction
• Displaying and Describing Data
• Statistical Inference
• Proportions, Frequencies, and Contingency Analysis
• Inference for One or Two Groups
• Data Transformations and Nonparametric Methods
• Designing Effective Experiments
• Inference for More than Two Groups
• Correlation and Regression
• Multiple Factors and Meta-Analysis
• Computer-Intensive Methods and Survival Analysis
• Multivariate Methods

## Required text and materials

The following textbook is required for this course:

1. Whitlock MC, Schluter D. 2020. The analysis of biological data, 3rd edition. W. H. Freeman.
Type: Textbook ISBN: 978-1-319-22623-7

• R Statistical Software and RStudio. Details on how to install and download can be found within the course after registration.

## Assessments

To complete this course successfully, students must achieve a passing grade of 50% or higher on the course overall and 50% or higher on the mandatory Final Project.

 Assignment 1: Lessons 1-3 8% Quiz 1: R Tutorials 1-3 8% Assignment 2: Lessons 4-6 8% Quiz 2: R Tutorials 4-6 8% Assignment 3: Lessons 7-9 8% Quiz 3: R Tutorials 7-9 8% Assignment 4: Lessons 10-12 8% Quiz 4: R Tutorials 10-12 8% Final Project (mandatory) 36%

## Open Learning Faculty Member Information

An Open Learning Faculty Member is available to assist students. Students will receive the necessary contact information at the start of the course.

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