B1834 - Biostatistics

Learning outcomes

At the end of the course, the student will know the statistical techniques applied to agricultural biotechnology. In addition to acquiring basic knowledge of descriptive statistics, the student will understand the logic of statistical inference and will be able to apply the most common statistical tests in research and the profession of an agricultural biotechnologist. The student will also be able to perform statistical analyses with dedicated software and interpret the output in the context of the analyzed phenomenon or experiment.

Course contents

Module 1

 

Introduction to Statistics

• Course organization

• Applications of statistics in plant biotechnology

• Science and pseudo-science

• Designing an experiment

 

Descriptive Statistics

• Types of data and variables

• Data visualization

• Describing data

 

Estimates and Uncertainty

• Sampling distribution

• Uncertainty of an estimate

• Confidence interval

 

Hypothesis Testing

• Designing hypotheses

• Hypothesis testing

• Errors in hypothesis testing

• Confidence intervals

 

Probability

• Probability distributions

• Independence and the product rule

• Conditional probability

Module 2

 

Proportions and Frequencies

• Binomial distribution

• Chi-square test

• Relative risk and odds ratio

• Fisher’s exact test

 

Comparison of Numerical Values

• Normal distribution

• Inference in a single population

• Comparison between two means

• Non-parametric tests

• Comparison of means across more than two groups

The use of R software will be a constant feature of both Modules 1 and 2.

Readings/Bibliography

Analisi statistica dei dati biologici, Michael C. Whitlock and Dolph Schluter (Zanichelli)

Statistica di base. Come, quando, perché, Fulvia Mecatti (McGraw-Hill Education)

Teaching methods

For each topic covered, the course includes a theoretical part and a practical part, which comprises applications in the agronomic sector. The course will provide the basics for using the R software, available at https://cran.r-project.org/ for all operating systems.

Assessment methods

The exam aims to assess the level of knowledge and understanding of the program's topics and the reasoning skills developed by the student. A written exam will be conducted over 2 hours, consisting of multiple-choice questions, open-ended questions, and problem-solving exercises.

Teaching tools

The course materials (PowerPoint presentations, exercises and solutions, and any recommended further readings) will be available on the Online Teaching website https://iol.unibo.it/ .

Access is restricted to students enrolled in the course.

Students with learning disorders and\or temporary or permanent disabilities: please, contact the office responsible (https://site.unibo.it/studenti-con-disabilita-e-dsa/en/for-students ) as soon as possible so that they can propose acceptable adjustments. The request for adaptation must be submitted in advance (15 days before the exam date) to the lecturer, who will assess the appropriateness of the adjustments, taking into account the teaching objectives.

Office hours

See the website of Francesco Chemello

See the website of Giorgio Milazzo