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    BIO 439/539: Big Data Analysis
    Course materials for BIO 439/539: Big Data Analysis
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    Statistics for Biologists
    There is no disputing the importance of statistical analysis in biological research, but too often it is considered only after an experiment is completed, when it may be too late.
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    An Introduction to Statistical Learning: with Applications in R
    This book provides an introduction to statistical learning methods and is aimed for upper level undergraduate students, masters students and Ph.D. students in the non-mathematical sciences.
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    R for biologists
    An introductory guide to data analysis in R for life sciences researchers.

    Keywords: R

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    Statistical Exploration of Climate Data
    In this module the students will learn some basic concepts in statistical thinking about data, with emphasis on exploratory data analysis.
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    Data Analysis for the Life Sciences
    An online stats book written completely in R
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    Continuous Growth Models
    This Excel worksheet compares user-input growth data with predictions under linear, exponential, and logistic models of growth. Introduces concepts of statistical analysis that can be additionally...
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    Java Applets for Power and Sample Size
    This is a Java application that allows you to do power and sample-size calculations for a number of standard statistical models.
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    The Human Microbiome Biodiversity in Health and Disease
    The students will analyze the human gut and vaginal microbiomes in healthy and diseased states using diversity of bacteria as determined by 16SrRNA sequence.
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    RNAseq data analysis using Galaxy
    This is a bioinformatics exercise intended for use in a computer lab setting with life science majors.
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    2007-Helfgott-Seier-Some Mathematical and Statistical Aspects of Enzyme Kinetics
    We will analyze some basic ideas behind enzyme kinetics, which allow us to deal with separable and linear differential equations as well as realize the need to use power series.
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    Spreadsheet Data Analysis Tutorial Series
    This series of self-paced tutorials show how to analyze data using a spreadsheet program.
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    Introduction to Quantitative Biology - Fall 2014 Syllabus
    Syllabus for Introduction to Quantitative Biology taught at the College of William and Mary.

    Keywords: quant biosyllabus

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    The effects of Avian Malaria On Pigeon Fledging Growth
    Poster on a case that combined Biology and Statistics in a student research project presented at the 2018 QUBES/BioQUEST Summer Workshop
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    Climate change and Strawberries: A real-life problem-based activity for teaching ANOVA
    This is a real-life lab activity for teaching ANOVA using Problem-Based Learning and formatted for one-day (JMP or R) or two-day (JMP) implementations.
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    Module M.8 Survival analysis
    Introduction to Primate Data Exploration and Linear Modeling with R was created with the goal of providing training to undergraduate biology students on data management and statistical analysis...
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    The nose knows: How tri-trophic interactions and natural history shape bird foraging behavior. An introduction to statistical analysis in animal behavior research
    Students investigate the role of olfaction and infochemicals on bird foraging behavior through two different quantitative activities where they generate hypotheses, create figures, conduct data...
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    Module M.4 Simple linear regression analysis
    Introduction to Primate Data Exploration and Linear Modeling with R was created with the goal of providing training to undergraduate biology students on data management and statistical analysis...
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    Exploring EnvironmenATL Justice with Data Analytics and Visualization
    Basic data handling and data analysis skills are introduced to visualize and analyze ‘big data.’ Environmental justice is introduced to give students an understanding of tools and strategies to...
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    2017-D_Goulet-Modeling, Simulating, and Parameter Fitting of Biochemical Kinetic Experiments
    In many chemical and biological applications, systems of differential equations containing unknown parameters are used to explain empirical observations and experimental data. The differential...
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